CINXE.COM
Deep Learning in Cancer Diagnostics: Predicting Outcomes from Histology and Genomics – Histology
<!DOCTYPE html> <html lang="en-US"> <head> <meta charset="UTF-8"> <title>Deep Learning in Cancer Diagnostics: Predicting Outcomes from Histology and Genomics – Histology</title> <meta name='robots' content='max-image-preview:large' /> <style>img:is([sizes="auto" i], [sizes^="auto," i]) { contain-intrinsic-size: 3000px 1500px }</style> <meta name="viewport" content="width=device-width, initial-scale=1"><link href='https://fonts.gstatic.com' crossorigin rel='preconnect' /> <link href='https://fonts.googleapis.com' crossorigin rel='preconnect' /> <link rel="alternate" type="application/rss+xml" title="Histology » Feed" href="https://histology.blog/archive/feed/" /> <script> window._wpemojiSettings = {"baseUrl":"https:\/\/s.w.org\/images\/core\/emoji\/15.0.3\/72x72\/","ext":".png","svgUrl":"https:\/\/s.w.org\/images\/core\/emoji\/15.0.3\/svg\/","svgExt":".svg","source":{"concatemoji":"https:\/\/histology.blog\/archive\/wp-includes\/js\/wp-emoji-release.min.js?ver=6.7.1"}}; /*! This file is auto-generated */ !function(i,n){var o,s,e;function c(e){try{var t={supportTests:e,timestamp:(new Date).valueOf()};sessionStorage.setItem(o,JSON.stringify(t))}catch(e){}}function p(e,t,n){e.clearRect(0,0,e.canvas.width,e.canvas.height),e.fillText(t,0,0);var t=new Uint32Array(e.getImageData(0,0,e.canvas.width,e.canvas.height).data),r=(e.clearRect(0,0,e.canvas.width,e.canvas.height),e.fillText(n,0,0),new Uint32Array(e.getImageData(0,0,e.canvas.width,e.canvas.height).data));return t.every(function(e,t){return e===r[t]})}function u(e,t,n){switch(t){case"flag":return n(e,"\ud83c\udff3\ufe0f\u200d\u26a7\ufe0f","\ud83c\udff3\ufe0f\u200b\u26a7\ufe0f")?!1:!n(e,"\ud83c\uddfa\ud83c\uddf3","\ud83c\uddfa\u200b\ud83c\uddf3")&&!n(e,"\ud83c\udff4\udb40\udc67\udb40\udc62\udb40\udc65\udb40\udc6e\udb40\udc67\udb40\udc7f","\ud83c\udff4\u200b\udb40\udc67\u200b\udb40\udc62\u200b\udb40\udc65\u200b\udb40\udc6e\u200b\udb40\udc67\u200b\udb40\udc7f");case"emoji":return!n(e,"\ud83d\udc26\u200d\u2b1b","\ud83d\udc26\u200b\u2b1b")}return!1}function f(e,t,n){var r="undefined"!=typeof WorkerGlobalScope&&self instanceof WorkerGlobalScope?new OffscreenCanvas(300,150):i.createElement("canvas"),a=r.getContext("2d",{willReadFrequently:!0}),o=(a.textBaseline="top",a.font="600 32px Arial",{});return e.forEach(function(e){o[e]=t(a,e,n)}),o}function t(e){var t=i.createElement("script");t.src=e,t.defer=!0,i.head.appendChild(t)}"undefined"!=typeof Promise&&(o="wpEmojiSettingsSupports",s=["flag","emoji"],n.supports={everything:!0,everythingExceptFlag:!0},e=new Promise(function(e){i.addEventListener("DOMContentLoaded",e,{once:!0})}),new Promise(function(t){var n=function(){try{var e=JSON.parse(sessionStorage.getItem(o));if("object"==typeof e&&"number"==typeof e.timestamp&&(new Date).valueOf()<e.timestamp+604800&&"object"==typeof e.supportTests)return e.supportTests}catch(e){}return null}();if(!n){if("undefined"!=typeof Worker&&"undefined"!=typeof OffscreenCanvas&&"undefined"!=typeof URL&&URL.createObjectURL&&"undefined"!=typeof Blob)try{var e="postMessage("+f.toString()+"("+[JSON.stringify(s),u.toString(),p.toString()].join(",")+"));",r=new Blob([e],{type:"text/javascript"}),a=new Worker(URL.createObjectURL(r),{name:"wpTestEmojiSupports"});return void(a.onmessage=function(e){c(n=e.data),a.terminate(),t(n)})}catch(e){}c(n=f(s,u,p))}t(n)}).then(function(e){for(var t in e)n.supports[t]=e[t],n.supports.everything=n.supports.everything&&n.supports[t],"flag"!==t&&(n.supports.everythingExceptFlag=n.supports.everythingExceptFlag&&n.supports[t]);n.supports.everythingExceptFlag=n.supports.everythingExceptFlag&&!n.supports.flag,n.DOMReady=!1,n.readyCallback=function(){n.DOMReady=!0}}).then(function(){return e}).then(function(){var e;n.supports.everything||(n.readyCallback(),(e=n.source||{}).concatemoji?t(e.concatemoji):e.wpemoji&&e.twemoji&&(t(e.twemoji),t(e.wpemoji)))}))}((window,document),window._wpemojiSettings); </script> <style id='wp-emoji-styles-inline-css'> img.wp-smiley, img.emoji { display: inline !important; border: none !important; box-shadow: none !important; height: 1em !important; width: 1em !important; margin: 0 0.07em !important; vertical-align: -0.1em !important; background: none !important; padding: 0 !important; } </style> <link rel='stylesheet' id='wp-block-library-css' href='https://histology.blog/archive/wp-includes/css/dist/block-library/style.min.css?ver=6.7.1' media='all' /> <style id='classic-theme-styles-inline-css'> /*! This file is auto-generated */ .wp-block-button__link{color:#fff;background-color:#32373c;border-radius:9999px;box-shadow:none;text-decoration:none;padding:calc(.667em + 2px) calc(1.333em + 2px);font-size:1.125em}.wp-block-file__button{background:#32373c;color:#fff;text-decoration:none} </style> <style id='global-styles-inline-css'> :root{--wp--preset--aspect-ratio--square: 1;--wp--preset--aspect-ratio--4-3: 4/3;--wp--preset--aspect-ratio--3-4: 3/4;--wp--preset--aspect-ratio--3-2: 3/2;--wp--preset--aspect-ratio--2-3: 2/3;--wp--preset--aspect-ratio--16-9: 16/9;--wp--preset--aspect-ratio--9-16: 9/16;--wp--preset--color--black: #000000;--wp--preset--color--cyan-bluish-gray: #abb8c3;--wp--preset--color--white: #ffffff;--wp--preset--color--pale-pink: #f78da7;--wp--preset--color--vivid-red: #cf2e2e;--wp--preset--color--luminous-vivid-orange: #ff6900;--wp--preset--color--luminous-vivid-amber: #fcb900;--wp--preset--color--light-green-cyan: #7bdcb5;--wp--preset--color--vivid-green-cyan: #00d084;--wp--preset--color--pale-cyan-blue: #8ed1fc;--wp--preset--color--vivid-cyan-blue: #0693e3;--wp--preset--color--vivid-purple: #9b51e0;--wp--preset--color--contrast: var(--contrast);--wp--preset--color--contrast-2: var(--contrast-2);--wp--preset--color--contrast-3: var(--contrast-3);--wp--preset--color--base: var(--base);--wp--preset--color--base-2: var(--base-2);--wp--preset--color--base-3: var(--base-3);--wp--preset--color--accent: var(--accent);--wp--preset--color--accent-2: var(--accent-2);--wp--preset--color--accent-hover: var(--accent-hover);--wp--preset--color--highlight: var(--highlight);--wp--preset--gradient--vivid-cyan-blue-to-vivid-purple: linear-gradient(135deg,rgba(6,147,227,1) 0%,rgb(155,81,224) 100%);--wp--preset--gradient--light-green-cyan-to-vivid-green-cyan: linear-gradient(135deg,rgb(122,220,180) 0%,rgb(0,208,130) 100%);--wp--preset--gradient--luminous-vivid-amber-to-luminous-vivid-orange: linear-gradient(135deg,rgba(252,185,0,1) 0%,rgba(255,105,0,1) 100%);--wp--preset--gradient--luminous-vivid-orange-to-vivid-red: linear-gradient(135deg,rgba(255,105,0,1) 0%,rgb(207,46,46) 100%);--wp--preset--gradient--very-light-gray-to-cyan-bluish-gray: linear-gradient(135deg,rgb(238,238,238) 0%,rgb(169,184,195) 100%);--wp--preset--gradient--cool-to-warm-spectrum: linear-gradient(135deg,rgb(74,234,220) 0%,rgb(151,120,209) 20%,rgb(207,42,186) 40%,rgb(238,44,130) 60%,rgb(251,105,98) 80%,rgb(254,248,76) 100%);--wp--preset--gradient--blush-light-purple: linear-gradient(135deg,rgb(255,206,236) 0%,rgb(152,150,240) 100%);--wp--preset--gradient--blush-bordeaux: linear-gradient(135deg,rgb(254,205,165) 0%,rgb(254,45,45) 50%,rgb(107,0,62) 100%);--wp--preset--gradient--luminous-dusk: linear-gradient(135deg,rgb(255,203,112) 0%,rgb(199,81,192) 50%,rgb(65,88,208) 100%);--wp--preset--gradient--pale-ocean: linear-gradient(135deg,rgb(255,245,203) 0%,rgb(182,227,212) 50%,rgb(51,167,181) 100%);--wp--preset--gradient--electric-grass: linear-gradient(135deg,rgb(202,248,128) 0%,rgb(113,206,126) 100%);--wp--preset--gradient--midnight: linear-gradient(135deg,rgb(2,3,129) 0%,rgb(40,116,252) 100%);--wp--preset--font-size--small: 13px;--wp--preset--font-size--medium: 20px;--wp--preset--font-size--large: 36px;--wp--preset--font-size--x-large: 42px;--wp--preset--spacing--20: 0.44rem;--wp--preset--spacing--30: 0.67rem;--wp--preset--spacing--40: 1rem;--wp--preset--spacing--50: 1.5rem;--wp--preset--spacing--60: 2.25rem;--wp--preset--spacing--70: 3.38rem;--wp--preset--spacing--80: 5.06rem;--wp--preset--shadow--natural: 6px 6px 9px rgba(0, 0, 0, 0.2);--wp--preset--shadow--deep: 12px 12px 50px rgba(0, 0, 0, 0.4);--wp--preset--shadow--sharp: 6px 6px 0px rgba(0, 0, 0, 0.2);--wp--preset--shadow--outlined: 6px 6px 0px -3px rgba(255, 255, 255, 1), 6px 6px rgba(0, 0, 0, 1);--wp--preset--shadow--crisp: 6px 6px 0px rgba(0, 0, 0, 1);}:where(.is-layout-flex){gap: 0.5em;}:where(.is-layout-grid){gap: 0.5em;}body .is-layout-flex{display: flex;}.is-layout-flex{flex-wrap: wrap;align-items: center;}.is-layout-flex > :is(*, div){margin: 0;}body .is-layout-grid{display: grid;}.is-layout-grid > :is(*, div){margin: 0;}:where(.wp-block-columns.is-layout-flex){gap: 2em;}:where(.wp-block-columns.is-layout-grid){gap: 2em;}:where(.wp-block-post-template.is-layout-flex){gap: 1.25em;}:where(.wp-block-post-template.is-layout-grid){gap: 1.25em;}.has-black-color{color: var(--wp--preset--color--black) !important;}.has-cyan-bluish-gray-color{color: var(--wp--preset--color--cyan-bluish-gray) !important;}.has-white-color{color: var(--wp--preset--color--white) !important;}.has-pale-pink-color{color: var(--wp--preset--color--pale-pink) !important;}.has-vivid-red-color{color: var(--wp--preset--color--vivid-red) !important;}.has-luminous-vivid-orange-color{color: var(--wp--preset--color--luminous-vivid-orange) !important;}.has-luminous-vivid-amber-color{color: var(--wp--preset--color--luminous-vivid-amber) !important;}.has-light-green-cyan-color{color: var(--wp--preset--color--light-green-cyan) !important;}.has-vivid-green-cyan-color{color: var(--wp--preset--color--vivid-green-cyan) !important;}.has-pale-cyan-blue-color{color: var(--wp--preset--color--pale-cyan-blue) !important;}.has-vivid-cyan-blue-color{color: var(--wp--preset--color--vivid-cyan-blue) !important;}.has-vivid-purple-color{color: var(--wp--preset--color--vivid-purple) !important;}.has-black-background-color{background-color: var(--wp--preset--color--black) !important;}.has-cyan-bluish-gray-background-color{background-color: var(--wp--preset--color--cyan-bluish-gray) !important;}.has-white-background-color{background-color: var(--wp--preset--color--white) !important;}.has-pale-pink-background-color{background-color: var(--wp--preset--color--pale-pink) !important;}.has-vivid-red-background-color{background-color: var(--wp--preset--color--vivid-red) !important;}.has-luminous-vivid-orange-background-color{background-color: var(--wp--preset--color--luminous-vivid-orange) !important;}.has-luminous-vivid-amber-background-color{background-color: var(--wp--preset--color--luminous-vivid-amber) !important;}.has-light-green-cyan-background-color{background-color: var(--wp--preset--color--light-green-cyan) !important;}.has-vivid-green-cyan-background-color{background-color: var(--wp--preset--color--vivid-green-cyan) !important;}.has-pale-cyan-blue-background-color{background-color: var(--wp--preset--color--pale-cyan-blue) !important;}.has-vivid-cyan-blue-background-color{background-color: var(--wp--preset--color--vivid-cyan-blue) !important;}.has-vivid-purple-background-color{background-color: var(--wp--preset--color--vivid-purple) !important;}.has-black-border-color{border-color: var(--wp--preset--color--black) !important;}.has-cyan-bluish-gray-border-color{border-color: var(--wp--preset--color--cyan-bluish-gray) !important;}.has-white-border-color{border-color: var(--wp--preset--color--white) !important;}.has-pale-pink-border-color{border-color: var(--wp--preset--color--pale-pink) !important;}.has-vivid-red-border-color{border-color: var(--wp--preset--color--vivid-red) !important;}.has-luminous-vivid-orange-border-color{border-color: var(--wp--preset--color--luminous-vivid-orange) !important;}.has-luminous-vivid-amber-border-color{border-color: var(--wp--preset--color--luminous-vivid-amber) !important;}.has-light-green-cyan-border-color{border-color: var(--wp--preset--color--light-green-cyan) !important;}.has-vivid-green-cyan-border-color{border-color: var(--wp--preset--color--vivid-green-cyan) !important;}.has-pale-cyan-blue-border-color{border-color: var(--wp--preset--color--pale-cyan-blue) !important;}.has-vivid-cyan-blue-border-color{border-color: var(--wp--preset--color--vivid-cyan-blue) !important;}.has-vivid-purple-border-color{border-color: var(--wp--preset--color--vivid-purple) !important;}.has-vivid-cyan-blue-to-vivid-purple-gradient-background{background: var(--wp--preset--gradient--vivid-cyan-blue-to-vivid-purple) !important;}.has-light-green-cyan-to-vivid-green-cyan-gradient-background{background: var(--wp--preset--gradient--light-green-cyan-to-vivid-green-cyan) !important;}.has-luminous-vivid-amber-to-luminous-vivid-orange-gradient-background{background: var(--wp--preset--gradient--luminous-vivid-amber-to-luminous-vivid-orange) !important;}.has-luminous-vivid-orange-to-vivid-red-gradient-background{background: var(--wp--preset--gradient--luminous-vivid-orange-to-vivid-red) !important;}.has-very-light-gray-to-cyan-bluish-gray-gradient-background{background: var(--wp--preset--gradient--very-light-gray-to-cyan-bluish-gray) !important;}.has-cool-to-warm-spectrum-gradient-background{background: var(--wp--preset--gradient--cool-to-warm-spectrum) !important;}.has-blush-light-purple-gradient-background{background: var(--wp--preset--gradient--blush-light-purple) !important;}.has-blush-bordeaux-gradient-background{background: var(--wp--preset--gradient--blush-bordeaux) !important;}.has-luminous-dusk-gradient-background{background: var(--wp--preset--gradient--luminous-dusk) !important;}.has-pale-ocean-gradient-background{background: var(--wp--preset--gradient--pale-ocean) !important;}.has-electric-grass-gradient-background{background: var(--wp--preset--gradient--electric-grass) !important;}.has-midnight-gradient-background{background: var(--wp--preset--gradient--midnight) !important;}.has-small-font-size{font-size: var(--wp--preset--font-size--small) !important;}.has-medium-font-size{font-size: var(--wp--preset--font-size--medium) !important;}.has-large-font-size{font-size: var(--wp--preset--font-size--large) !important;}.has-x-large-font-size{font-size: var(--wp--preset--font-size--x-large) !important;} :where(.wp-block-post-template.is-layout-flex){gap: 1.25em;}:where(.wp-block-post-template.is-layout-grid){gap: 1.25em;} :where(.wp-block-columns.is-layout-flex){gap: 2em;}:where(.wp-block-columns.is-layout-grid){gap: 2em;} :root :where(.wp-block-pullquote){font-size: 1.5em;line-height: 1.6;} </style> <link rel='stylesheet' id='parent-style-css' href='https://histology.blog/archive/wp-content/themes/generatepress/style.css?ver=6.7.1' media='all' /> <link rel='stylesheet' id='generate-widget-areas-css' href='https://histology.blog/archive/wp-content/themes/generatepress/assets/css/components/widget-areas.min.css?ver=3.4.0' media='all' /> <link rel='stylesheet' id='generate-style-css' href='https://histology.blog/archive/wp-content/themes/generatepress/assets/css/main.min.css?ver=3.4.0' media='all' /> <style id='generate-style-inline-css'> body{background-color:var(--base);color:var(--contrast);}a{color:#1b78e2;}a:hover, a:focus, a:active{color:var(--accent-hover);}.wp-block-group__inner-container{max-width:1200px;margin-left:auto;margin-right:auto;}.site-header .header-image{width:200px;}:root{--contrast:#212121;--contrast-2:#2f4468;--contrast-3:#878787;--base:#fafafa;--base-2:#f7f8f9;--base-3:#ffffff;--accent:#242226;--accent-2:#1b78e2;--accent-hover:#35343a;--highlight:#83b0de;}:root .has-contrast-color{color:var(--contrast);}:root .has-contrast-background-color{background-color:var(--contrast);}:root .has-contrast-2-color{color:var(--contrast-2);}:root .has-contrast-2-background-color{background-color:var(--contrast-2);}:root .has-contrast-3-color{color:var(--contrast-3);}:root .has-contrast-3-background-color{background-color:var(--contrast-3);}:root .has-base-color{color:var(--base);}:root .has-base-background-color{background-color:var(--base);}:root .has-base-2-color{color:var(--base-2);}:root .has-base-2-background-color{background-color:var(--base-2);}:root .has-base-3-color{color:var(--base-3);}:root .has-base-3-background-color{background-color:var(--base-3);}:root .has-accent-color{color:var(--accent);}:root .has-accent-background-color{background-color:var(--accent);}:root .has-accent-2-color{color:var(--accent-2);}:root .has-accent-2-background-color{background-color:var(--accent-2);}:root .has-accent-hover-color{color:var(--accent-hover);}:root .has-accent-hover-background-color{background-color:var(--accent-hover);}:root .has-highlight-color{color:var(--highlight);}:root .has-highlight-background-color{background-color:var(--highlight);}.gp-modal:not(.gp-modal--open):not(.gp-modal--transition){display:none;}.gp-modal--transition:not(.gp-modal--open){pointer-events:none;}.gp-modal-overlay:not(.gp-modal-overlay--open):not(.gp-modal--transition){display:none;}.gp-modal__overlay{display:none;position:fixed;top:0;left:0;right:0;bottom:0;background:rgba(0,0,0,0.2);display:flex;justify-content:center;align-items:center;z-index:10000;backdrop-filter:blur(3px);transition:opacity 500ms ease;opacity:0;}.gp-modal--open:not(.gp-modal--transition) .gp-modal__overlay{opacity:1;}.gp-modal__container{max-width:100%;max-height:100vh;transform:scale(0.9);transition:transform 500ms ease;padding:0 10px;}.gp-modal--open:not(.gp-modal--transition) .gp-modal__container{transform:scale(1);}.search-modal-fields{display:flex;}.gp-search-modal .gp-modal__overlay{align-items:flex-start;padding-top:25vh;background:var(--gp-search-modal-overlay-bg-color);}.search-modal-form{width:500px;max-width:100%;background-color:var(--gp-search-modal-bg-color);color:var(--gp-search-modal-text-color);}.search-modal-form .search-field, .search-modal-form .search-field:focus{width:100%;height:60px;background-color:transparent;border:0;appearance:none;color:currentColor;}.search-modal-fields button, .search-modal-fields button:active, .search-modal-fields button:focus, .search-modal-fields button:hover{background-color:transparent;border:0;color:currentColor;width:60px;}body, button, input, select, textarea{font-family:Open Sans, sans-serif;font-size:17px;}.main-title{font-size:25px;}.widget-title{font-weight:600;}button:not(.menu-toggle),html input[type="button"],input[type="reset"],input[type="submit"],.button,.wp-block-button .wp-block-button__link{font-size:15px;}h1{font-weight:600;font-size:40px;}h2{font-weight:600;font-size:30px;}h3{font-size:20px;}.top-bar{background-color:#636363;color:#ffffff;}.top-bar a{color:#ffffff;}.top-bar a:hover{color:#303030;}.site-header{background-color:#ffffff;color:#3a3a3a;}.site-header a{color:#3a3a3a;}.main-title a,.main-title a:hover{color:#ffffff;}.site-description{color:#757575;}.main-navigation,.main-navigation ul ul{background-color:var(--base);}.main-navigation .main-nav ul li a, .main-navigation .menu-toggle, .main-navigation .menu-bar-items{color:var(--contrast);}.main-navigation .main-nav ul li:not([class*="current-menu-"]):hover > a, .main-navigation .main-nav ul li:not([class*="current-menu-"]):focus > a, .main-navigation .main-nav ul li.sfHover:not([class*="current-menu-"]) > a, .main-navigation .menu-bar-item:hover > a, .main-navigation .menu-bar-item.sfHover > a{color:var(--base-3);background-color:var(--contrast);}button.menu-toggle:hover,button.menu-toggle:focus{color:var(--contrast);}.main-navigation .main-nav ul li[class*="current-menu-"] > a{color:var(--base-3);background-color:var(--accent-hover);}.navigation-search input[type="search"],.navigation-search input[type="search"]:active, .navigation-search input[type="search"]:focus, .main-navigation .main-nav ul li.search-item.active > a, .main-navigation .menu-bar-items .search-item.active > a{color:var(--base-3);background-color:var(--contrast);}.separate-containers .inside-article, .separate-containers .comments-area, .separate-containers .page-header, .one-container .container, .separate-containers .paging-navigation, .inside-page-header{background-color:var(--base-3);}.inside-article a,.paging-navigation a,.comments-area a,.page-header a{color:var(--accent-2);}.inside-article a:hover,.paging-navigation a:hover,.comments-area a:hover,.page-header a:hover{color:var(--accent-hover);}.entry-title a{color:var(--contrast);}.entry-title a:hover{color:var(--accent-hover);}.entry-meta{color:var(--contrast-3);}.entry-meta a{color:var(--contrast);}.entry-meta a:hover{color:var(--accent-hover);}h1{color:var(--contrast);}h2{color:var(--contrast);}h3{color:var(--contrast);}.sidebar .widget{background-color:#ffffff;}.sidebar .widget a{color:var(--contrast);padding:0px;}.sidebar .widget a:hover{color:var(--accent-hover);}.sidebar .widget .widget-title{color:#000000;}.footer-widgets{color:var(--base-3);background-color:var(--contrast-2);}.footer-widgets a{color:var(--base-3);}.footer-widgets a:hover{color:var(--base-3);}.footer-widgets .widget-title{color:var(--base-2);}.site-info{color:var(--contrast-2);}.site-info a{color:var(--contrast-2);}.site-info a:hover{color:var(--accent-hover);}.footer-bar .widget_nav_menu .current-menu-item a{color:var(--accent-hover);}input[type="text"],input[type="email"],input[type="url"],input[type="password"],input[type="search"],input[type="tel"],input[type="number"],textarea,select{color:var(--contrast);background-color:#fafafa;border-color:var(--contrast);}input[type="text"]:focus,input[type="email"]:focus,input[type="url"]:focus,input[type="password"]:focus,input[type="search"]:focus,input[type="tel"]:focus,input[type="number"]:focus,textarea:focus,select:focus{color:var(--contrast-3);background-color:#ffffff;border-color:var(--contrast-3);}button,html input[type="button"],input[type="reset"],input[type="submit"],a.button,a.wp-block-button__link:not(.has-background){color:#ffffff;background-color:var(--accent);}button:hover,html input[type="button"]:hover,input[type="reset"]:hover,input[type="submit"]:hover,a.button:hover,button:focus,html input[type="button"]:focus,input[type="reset"]:focus,input[type="submit"]:focus,a.button:focus,a.wp-block-button__link:not(.has-background):active,a.wp-block-button__link:not(.has-background):focus,a.wp-block-button__link:not(.has-background):hover{color:#ffffff;background-color:var(--accent-hover);}a.generate-back-to-top{background-color:rgba( 0,0,0,0.4 );color:#ffffff;}a.generate-back-to-top:hover,a.generate-back-to-top:focus{background-color:rgba( 0,0,0,0.6 );color:#ffffff;}:root{--gp-search-modal-bg-color:var(--base-3);--gp-search-modal-text-color:var(--contrast);--gp-search-modal-overlay-bg-color:rgba(0,0,0,0.2);}@media (max-width: 768px){.main-navigation .menu-bar-item:hover > a, .main-navigation .menu-bar-item.sfHover > a{background:none;color:var(--contrast);}}.inside-top-bar{padding:10px;}.inside-header{padding:40px;}.nav-below-header .main-navigation .inside-navigation.grid-container, .nav-above-header .main-navigation .inside-navigation.grid-container{padding:0px 20px 0px 20px;}.separate-containers .inside-article, .separate-containers .comments-area, .separate-containers .page-header, .separate-containers .paging-navigation, .one-container .site-content, .inside-page-header{padding:50px;}.site-main .wp-block-group__inner-container{padding:50px;}.separate-containers .paging-navigation{padding-top:20px;padding-bottom:20px;}.entry-content .alignwide, body:not(.no-sidebar) .entry-content .alignfull{margin-left:-50px;width:calc(100% + 100px);max-width:calc(100% + 100px);}.one-container.right-sidebar .site-main,.one-container.both-right .site-main{margin-right:50px;}.one-container.left-sidebar .site-main,.one-container.both-left .site-main{margin-left:50px;}.one-container.both-sidebars .site-main{margin:0px 50px 0px 50px;}.one-container.archive .post:not(:last-child):not(.is-loop-template-item), .one-container.blog .post:not(:last-child):not(.is-loop-template-item){padding-bottom:50px;}.main-navigation .main-nav ul li a,.menu-toggle,.main-navigation .menu-bar-item > a{line-height:51px!important;}.navigation-search input[type="search"]{height:65px;}.rtl .menu-item-has-children .dropdown-menu-toggle{padding-left:20px;}.rtl .main-navigation .main-nav ul li.menu-item-has-children > a{padding-right:20px;}.widget-area .widget{padding:50px;}.inside-site-info{padding:20px;}@media (max-width:768px){.separate-containers .inside-article, .separate-containers .comments-area, .separate-containers .page-header, .separate-containers .paging-navigation, .one-container .site-content, .inside-page-header{padding:30px;}.site-main .wp-block-group__inner-container{padding:30px;}.inside-site-info{padding-right:10px;padding-left:10px;}.entry-content .alignwide, body:not(.no-sidebar) .entry-content .alignfull{margin-left:-30px;width:calc(100% + 60px);max-width:calc(100% + 60px);}.one-container .site-main .paging-navigation{margin-bottom:20px;}.main-navigation ul ul{background-color:var(--base)!important;}.main-navigation.toggled .main-nav > ul{background-color:var(--base)!important;}}/* End cached CSS */.is-right-sidebar{width:30%;}.is-left-sidebar{width:25%;}.site-content .content-area{width:70%;}@media (max-width: 768px){.main-navigation .menu-toggle,.sidebar-nav-mobile:not(#sticky-placeholder){display:block;}.main-navigation ul,.gen-sidebar-nav,.main-navigation:not(.slideout-navigation):not(.toggled) .main-nav > ul,.has-inline-mobile-toggle #site-navigation .inside-navigation > *:not(.navigation-search):not(.main-nav){display:none;}.nav-align-right .inside-navigation,.nav-align-center .inside-navigation{justify-content:space-between;}} .dynamic-author-image-rounded{border-radius:100%;}.dynamic-featured-image, .dynamic-author-image{vertical-align:middle;}.one-container.blog .dynamic-content-template:not(:last-child), .one-container.archive .dynamic-content-template:not(:last-child){padding-bottom:0px;}.dynamic-entry-excerpt > p:last-child{margin-bottom:0px;} .main-navigation .main-nav ul li a,.menu-toggle,.main-navigation .menu-bar-item > a{transition: line-height 300ms ease}.main-navigation.toggled .main-nav > ul{background-color: var(--accent)}.sticky-enabled .gen-sidebar-nav.is_stuck .main-navigation {margin-bottom: 0px;}.sticky-enabled .gen-sidebar-nav.is_stuck {z-index: 500;}.sticky-enabled .main-navigation.is_stuck {box-shadow: 0 2px 2px -2px rgba(0, 0, 0, .2);}.navigation-stick:not(.gen-sidebar-nav) {left: 0;right: 0;width: 100% !important;}.nav-float-right .navigation-stick {width: 100% !important;left: 0;}.nav-float-right .navigation-stick .navigation-branding {margin-right: auto;}.main-navigation.has-sticky-branding:not(.grid-container) .inside-navigation:not(.grid-container) .navigation-branding{margin-left: 10px;} </style> <link rel='stylesheet' id='generate-child-css' href='https://histology.blog/archive/wp-content/themes/generatepress-child/style.css?ver=1724233037' media='all' /> <link rel='stylesheet' id='generate-google-fonts-css' href='https://fonts.googleapis.com/css?family=Open+Sans%3A300%2Cregular%2Citalic%2C600%2C700&display=auto&ver=3.4.0' media='all' /> <link rel='stylesheet' id='generate-blog-images-css' href='https://histology.blog/archive/wp-content/plugins/gp-premium/blog/functions/css/featured-images.min.css?ver=2.4.1' media='all' /> <link rel='stylesheet' id='generate-navigation-branding-css' href='https://histology.blog/archive/wp-content/plugins/gp-premium/menu-plus/functions/css/navigation-branding-flex.min.css?ver=2.4.1' media='all' /> <style id='generate-navigation-branding-inline-css'> .main-navigation.has-branding .inside-navigation.grid-container, .main-navigation.has-branding.grid-container .inside-navigation:not(.grid-container){padding:0px 50px 0px 50px;}.main-navigation.has-branding:not(.grid-container) .inside-navigation:not(.grid-container) .navigation-branding{margin-left:10px;}.navigation-branding img, .site-logo.mobile-header-logo img{height:65px;width:auto;}.navigation-branding .main-title{line-height:65px;}@media (max-width: 768px){.main-navigation.has-branding.nav-align-center .menu-bar-items, .main-navigation.has-sticky-branding.navigation-stick.nav-align-center .menu-bar-items{margin-left:auto;}.navigation-branding{margin-right:auto;margin-left:10px;}.navigation-branding .main-title, .mobile-header-navigation .site-logo{margin-left:10px;}.main-navigation.has-branding .inside-navigation.grid-container{padding:0px;}} </style> <script src="https://histology.blog/archive/wp-includes/js/jquery/jquery.min.js?ver=3.7.1" id="jquery-core-js"></script> <link rel="https://api.w.org/" href="https://histology.blog/archive/wp-json/" /><link rel="alternate" title="JSON" type="application/json" href="https://histology.blog/archive/wp-json/wp/v2/posts/71" /><link rel="EditURI" type="application/rsd+xml" title="RSD" href="https://histology.blog/archive/xmlrpc.php?rsd" /> <meta name="generator" content="WordPress 6.7.1" /> <link rel="canonical" href="https://histology.blog/archive/cancer-diagnostics/deep-learning-in-cancer-diagnostics-predicting-outcomes-from-histology-and-genomics/" /> <link rel='shortlink' href='https://histology.blog/archive/?p=71' /> <link rel="alternate" title="oEmbed (JSON)" type="application/json+oembed" href="https://histology.blog/archive/wp-json/oembed/1.0/embed?url=https%3A%2F%2Fhistology.blog%2Farchive%2Fcancer-diagnostics%2Fdeep-learning-in-cancer-diagnostics-predicting-outcomes-from-histology-and-genomics%2F" /> <link rel="alternate" title="oEmbed (XML)" type="text/xml+oembed" href="https://histology.blog/archive/wp-json/oembed/1.0/embed?url=https%3A%2F%2Fhistology.blog%2Farchive%2Fcancer-diagnostics%2Fdeep-learning-in-cancer-diagnostics-predicting-outcomes-from-histology-and-genomics%2F&format=xml" /> <link rel="icon" href="https://histology.blog/archive/wp-content/uploads/2024/08/cropped-favi-icon-32x32.png" sizes="32x32" /> <link rel="icon" href="https://histology.blog/archive/wp-content/uploads/2024/08/cropped-favi-icon-192x192.png" sizes="192x192" /> <link rel="apple-touch-icon" href="https://histology.blog/archive/wp-content/uploads/2024/08/cropped-favi-icon-180x180.png" /> <meta name="msapplication-TileImage" content="https://histology.blog/archive/wp-content/uploads/2024/08/cropped-favi-icon-270x270.png" /> </head> <body class="post-template-default single single-post postid-71 single-format-standard wp-custom-logo wp-embed-responsive post-image-above-header post-image-aligned-center sticky-menu-no-transition sticky-enabled both-sticky-menu right-sidebar nav-below-header separate-containers header-aligned-left dropdown-hover featured-image-active" itemtype="https://schema.org/Blog" itemscope> <a class="screen-reader-text skip-link" href="#content" title="Skip to content">Skip to content</a> <nav class="auto-hide-sticky has-branding main-navigation nav-align-right has-menu-bar-items sub-menu-right" id="site-navigation" aria-label="Primary" itemtype="https://schema.org/SiteNavigationElement" itemscope> <div class="inside-navigation grid-container"> <div class="navigation-branding"><div class="site-logo"> <a href="https://histology.blog/archive/" title="Histology" rel="home"> <img class="header-image is-logo-image" alt="Histology" src="https://histology.blog/archive/wp-content/uploads/2024/08/cropped-logo.png" title="Histology" width="739" height="213" /> </a> </div></div> <button class="menu-toggle" aria-controls="primary-menu" aria-expanded="false"> <span class="gp-icon icon-menu-bars"><svg viewBox="0 0 512 512" aria-hidden="true" xmlns="http://www.w3.org/2000/svg" width="1em" height="1em"><path d="M0 96c0-13.255 10.745-24 24-24h464c13.255 0 24 10.745 24 24s-10.745 24-24 24H24c-13.255 0-24-10.745-24-24zm0 160c0-13.255 10.745-24 24-24h464c13.255 0 24 10.745 24 24s-10.745 24-24 24H24c-13.255 0-24-10.745-24-24zm0 160c0-13.255 10.745-24 24-24h464c13.255 0 24 10.745 24 24s-10.745 24-24 24H24c-13.255 0-24-10.745-24-24z" /></svg><svg viewBox="0 0 512 512" aria-hidden="true" xmlns="http://www.w3.org/2000/svg" width="1em" height="1em"><path d="M71.029 71.029c9.373-9.372 24.569-9.372 33.942 0L256 222.059l151.029-151.03c9.373-9.372 24.569-9.372 33.942 0 9.372 9.373 9.372 24.569 0 33.942L289.941 256l151.03 151.029c9.372 9.373 9.372 24.569 0 33.942-9.373 9.372-24.569 9.372-33.942 0L256 289.941l-151.029 151.03c-9.373 9.372-24.569 9.372-33.942 0-9.372-9.373-9.372-24.569 0-33.942L222.059 256 71.029 104.971c-9.372-9.373-9.372-24.569 0-33.942z" /></svg></span><span class="mobile-menu">Menu</span> </button> <div id="primary-menu" class="main-nav"><ul id="menu-primary-menu" class=" menu sf-menu"><li id="menu-item-59" class="menu-item menu-item-type-custom menu-item-object-custom menu-item-59"><a href="https://histology.blog/">Home</a></li> <li id="menu-item-67" class="menu-item menu-item-type-custom menu-item-object-custom menu-item-67"><a href="https://histology.blog/about/">About</a></li> <li id="menu-item-60" class="menu-item menu-item-type-custom menu-item-object-custom menu-item-60"><a href="https://histology.blog/publication-trends/">Publication Trends</a></li> <li id="menu-item-61" class="menu-item menu-item-type-custom menu-item-object-custom menu-item-61"><a href="https://histology.blog/recent-publications/">Recent Publications</a></li> <li id="menu-item-62" class="menu-item menu-item-type-custom menu-item-object-custom menu-item-62"><a href="https://histology.blog/expert-search/">Expert Search</a></li> </ul></div><div class="menu-bar-items"> <span class="menu-bar-item"> <a href="#" role="button" aria-label="Open search" data-gpmodal-trigger="gp-search"><span class="gp-icon icon-search"><svg viewBox="0 0 512 512" aria-hidden="true" xmlns="http://www.w3.org/2000/svg" width="1em" height="1em"><path fill-rule="evenodd" clip-rule="evenodd" d="M208 48c-88.366 0-160 71.634-160 160s71.634 160 160 160 160-71.634 160-160S296.366 48 208 48zM0 208C0 93.125 93.125 0 208 0s208 93.125 208 208c0 48.741-16.765 93.566-44.843 129.024l133.826 134.018c9.366 9.379 9.355 24.575-.025 33.941-9.379 9.366-24.575 9.355-33.941-.025L337.238 370.987C301.747 399.167 256.839 416 208 416 93.125 416 0 322.875 0 208z" /></svg><svg viewBox="0 0 512 512" aria-hidden="true" xmlns="http://www.w3.org/2000/svg" width="1em" height="1em"><path d="M71.029 71.029c9.373-9.372 24.569-9.372 33.942 0L256 222.059l151.029-151.03c9.373-9.372 24.569-9.372 33.942 0 9.372 9.373 9.372 24.569 0 33.942L289.941 256l151.03 151.029c9.372 9.373 9.372 24.569 0 33.942-9.373 9.372-24.569 9.372-33.942 0L256 289.941l-151.029 151.03c-9.373 9.372-24.569 9.372-33.942 0-9.372-9.373-9.372-24.569 0-33.942L222.059 256 71.029 104.971c-9.372-9.373-9.372-24.569 0-33.942z" /></svg></span></a> </span> </div> </div> </nav> <div class="site grid-container container hfeed" id="page"> <div class="site-content" id="content"> <div class="content-area" id="primary"> <main class="site-main" id="main"> <article id="post-71" class="post-71 post type-post status-publish format-standard has-post-thumbnail hentry category-cancer-diagnostics tag-ai-in-healthcare tag-cancer-diagnostics tag-cancer-prognosis tag-convolutional-neural-networks tag-deep-learning tag-genomics tag-histopathology tag-personalized-medicine tag-predictive-biomarkers" itemtype="https://schema.org/CreativeWork" itemscope> <div class="inside-article"> <div class="featured-image page-header-image-single "> <img width="1200" height="628" src="https://histology.blog/archive/wp-content/uploads/2024/10/banner-17-min-scaled-e1727786157966.jpg" class="attachment-full size-full" alt="" itemprop="image" decoding="async" fetchpriority="high" /> </div> <header class="entry-header"> <h1 class="entry-title" itemprop="headline">Deep Learning in Cancer Diagnostics: Predicting Outcomes from Histology and Genomics</h1> <div class="entry-meta"> <span class="posted-on"><time class="entry-date published" datetime="2024-10-01T18:06:06+05:30" itemprop="datePublished">October 1, 2024</time></span> <span class="byline">by <span class="author vcard" itemprop="author" itemtype="https://schema.org/Person" itemscope><a class="url fn n" href="https://histology.blog/archive/author/histology/" title="View all posts by histology" rel="author" itemprop="url"><span class="author-name" itemprop="name">histology</span></a></span></span> </div> </header> <div class="entry-content" itemprop="text"> <h3><b>Introduction</b></h3> <p><span style="font-weight: 400;">Cancer is a group of diseases with diverse characteristics that remain a daunting clinical problem in the context of diagnosis, risk estimation, and therapy. Even today, determining the prognosis in cancer patients is still a challenge owing to intratumor heterogeneity and patients’ predisposition to therapy. Deep learning, which can largely be classified under AI, has recently emerged and brought with it tools applicable to cancer diagnosis that can analyze huge amounts of data, such as histological images and genomic data. Many DL models, especially CNNs, have proven their ability to extract relevant features from histopathological images and fuse genomic data to predict cancer development, treatment efficacy, and the patient’s survival. This blog introduces deep learning in different aspects of cancer diagnosis and how these complex algorithms are revolutionizing the way cancer is diagnosed and prognosis is made.</span></p> <h3><b>The Role of Histopathology and Genomics in Cancer Diagnosis</b></h3> <p><span style="font-weight: 400;">The laboratory method of examination of tissues for disease, notably cancer, through the lens of a microscope, has been around for over a century. This helps pathologists to determine the architectural and functional changes of tissues and whether there are tumor-facilitating changes, aggressiveness, and location. Genomic profiling, on the other hand, provides an understanding of the molecular nature of cancer by defining the genes and their products, altered expression, and other characteristics that determine tumor activity. Histopathological and genomic features provide a broad understanding of cancer, but interpreting and analyzing these multilayered datasets are subjective, time-consuming, and affected by inter-observer variability.</span></p> <p><span style="font-weight: 400;">Subsequent developments in improving deep learning ML capabilities have covered such a gap through the provision of computerized, accurate, and replicable approaches to histopathology and genomics analysis. It appears that deep learning models can be trained to detect complex patterns in histological slides that cannot be discerned by humans, as well as to identify relationships between such patterns and genomic changes, which makes for a systemic approach to cancer diagnosis.</span></p> <p></div></div> <div style="background: #f7f7f7;border: 1px solid rgba(0, 0, 0, 0.07);"> <div style="padding: 30px;"><div class="Adblock-main"> <div class="Adblock-head"> <h2>Yearwise Publication Trend on <b>“<a href="https://histology.blog/publication-trends/index/cancer diagnostics" target="_blank" title="cancer diagnostics - yearwise publication trends">cancer diagnostics</a>”</b></h2> </div> </div><div class="results-container"><div class="chart-block" style="padding:15px;"> <div class="left"> <div id="results" class="results"></div> </div> <div class="right"> <div class="chart-container"><canvas id="publicationChart"></canvas></div> </div> <div class="keywordsdiv"> <div style="text-align:center;"><b>Find publication trends on relevant topics</b> </div> <span class="gp-icon icon-tags"><svg viewBox="0 0 512 512" aria-hidden="true" xmlns="http://www.w3.org/2000/svg" width="1em" height="1em"><path d="M20 39.5c-8.836 0-16 7.163-16 16v176c0 4.243 1.686 8.313 4.687 11.314l224 224c6.248 6.248 16.378 6.248 22.626 0l176-176c6.244-6.244 6.25-16.364.013-22.615l-223.5-224A15.999 15.999 0 00196.5 39.5H20zm56 96c0-13.255 10.745-24 24-24s24 10.745 24 24-10.745 24-24 24-24-10.745-24-24z"></path><path d="M259.515 43.015c4.686-4.687 12.284-4.687 16.97 0l228 228c4.686 4.686 4.686 12.284 0 16.97l-180 180c-4.686 4.687-12.284 4.687-16.97 0-4.686-4.686-4.686-12.284 0-16.97L479.029 279.5 259.515 59.985c-4.686-4.686-4.686-12.284 0-16.97z"></path></svg></span> <span id="keyword-stats"></span> </div> </div></div></div><div class="inside-article"><style> table { margin: 0 0 1.5em; width: max-content; text-align: center; } @media only screen and (max-width: 993px) { .Adblock-main { width: 100% !important; margin:auto } } .Adblock-main { width: 100%; margin:auto; background-color:#fff; } .Adblock-head { background: #42c251; padding: 12px 10px; } .Adblock-head h1, .Adblock-head h2 { color: #fff; font-size: 20px; text-align: center; font-weight: 500; margin-bottom: 10px; margin-top: 8px; } .Adblock-head h1 a{ color: #000; text-decoration: none; font-size:22px; padding:0px; } .Adblock-head h1 a:hover{ color: #000; text-decoration: underline; } .Ad-title{ margin-bottom: 1px; margin-top: 5px; text-align: center; font-size: 15px; color: #000; } .Ad-title a { color: #000; text-decoration: underline; } .Ad-title a:hover{ color: #000; text-decoration: underline; } .Ad-title1 { margin-bottom: 0px; margin-top: 15px; text-align: center; font-size: 18px; color: #000; } .Ad-title1 a { color: #000; text-decoration: underline; } .Ad-title1 a:hover{ color: #000; text-decoration: underline; } .Ad-subtitle { margin-bottom: 8px; margin-top: 15px; text-align: center; } .Ad-subtitle1 { margin-bottom: 0px; margin-top: 10px; text-align: center; font-size: 16px; } .Ad-middle { border: solid 1px #ccc; padding-bottom: 20px; border-bottom: none; } .register-button { background-color: #283b39; color: #ffffff !important; padding: 10px 14px; border: none; border-radius: 5px; font-size: 14px; cursor: pointer; text-decoration: none; display: inline-block; margin-top: 15px; } .register-button span { color:#6dfe7e; } .register-button:hover { background-color: #161515; color:#fff; } .tablediv { width:100%; border: solid 1px #ccc; background:#fff; margin-bottom: 0px !important; } .tablediv th,.tablediv td{ font-size:13px!important; } .keywordsdiv { font-size: 14px; margin-bottom: 0px; background: #f1f1f1; padding: 10px 15px; margin-top: 15px; border-radius: 5px; } .keywordsdiv a{ color: #276cb5; padding: 0; } .keywordsdiv a:hover{ color:#000; text-decoration:underline; } .pub-scroll{ max-height: 260px; overflow-y: auto; overflow-x: hidden; } .chart-block { display: flex; flex-wrap: wrap; justify-content: space-between; background:#fff; border:1px solid #ccc; } .chart-block .left, .chart-block .right { background-color: #fff; padding: 20px; box-sizing: border-box; } .chart-block .left { flex: 1 1 5%; /* Takes up 45% of the width, flexible */ padding-right:0px !important } .chart-block .right { flex: 1 1 45%; /* Takes up 45% of the width, flexible */ } /* Responsive adjustments */ @media (max-width: 768px) { .chart-block .left, .chart-block .right { flex: 1 1 100%; /* Stack vertically on smaller screens */ margin: 0 0 10px 0; padding-right:20px !important } .chart-block .right{ width:50% !important; border:solid 1px #ccc; } .pub-scroll{ max-height:100% !important; overflow-y: inherit; overflow-x: hidden; } } </style> <script src='https://cdn.jsdelivr.net/npm/chart.js'></script> <script> var chart = null; function displayResults(statistics) { var resultsContainer = document.getElementById('results'); if (!statistics || Object.keys(statistics).length === 0) { resultsContainer.innerHTML = '<p>No data found.</p>'; return; } var tableHTML = `<div class='pub-scroll'> <table class='tablediv' border='1' cellspacing='0' cellpadding='0'> <tr> <th>Year</th> <th>Publication Count</th> </tr>`; Object.entries(statistics).sort(([yearA], [yearB]) => yearB - yearA).forEach(([year, count]) => { const displayCount = count === 0 ? 'NA' : count; tableHTML += ` <tr> <td>${year}</td> <td>${displayCount}</td> </tr> `; }); tableHTML += '</table></div>'; resultsContainer.innerHTML = tableHTML; } function displayLineChart(statistics) { var years = Object.keys(statistics); var counts = Object.values(statistics); var ctx = document.getElementById('publicationChart').getContext('2d'); // Destroy existing chart instance if it exists if (chart !== null) { chart.destroy(); } // Create a new chart instance chart = new Chart(ctx, { type: 'line', data: { labels: years, datasets: [{ label: 'Publication Counts', data: counts, fill: false, borderColor: 'rgba(75, 192, 192, 1)', tension: 0.1 }] }, options: { scales: { y: { beginAtZero: true } }, plugins: { legend: { display: true, position: 'top' } } } }); } function displayKeywordStats(keywords) { var resultsContainer = document.getElementById('keyword-stats'); resultsContainer.innerHTML = ''; if (!keywords || keywords.length === 0) { resultsContainer.innerHTML = '<p>No data found.</p>'; return; } var keywordHTML = ''; keywords.forEach((key, index) => { let key_replace = key.replace(/ /g, '-'); key_replace = key_replace.toLowerCase(); keywordHTML += `<a href="https://histology.blog/publication-trends/index/${key_replace}" target="_blank" title="${key} - yearwise publication trends">${key}</a>`; if (index < keywords.length - 1) { keywordHTML += ', '; } }); resultsContainer.innerHTML = keywordHTML; } // Call the function with the PHP data var statistics = { "2014": 211, "2015": 164, "2016": 245, "2017": 258, "2018": 272, "2019": 408, "2020": 537, "2021": 730, "2022": 982, "2023": 1597, "2024": 765 }; var keywordsArray = ["Deep learning","cancer diagnostics","histopathology","genomics","convolutional neural networks","predictive biomarkers","cancer prognosis","personalized medicine","AI in healthcare"]; displayResults(statistics); displayLineChart(statistics); displayKeywordStats(keywordsArray); </script></p> <h3><b>Deep Learning Models for Predicting Cancer Outcomes</b></h3> <p><span style="font-weight: 400;">This work demonstrated a very important use of the deep learning technique in cancer diagnostics based on histological picture, and genomics in determining patient outcomes. When operated on large datasets, deep learning models can also identify features for disease progression and the consequent treatment, as well as for the probability of survival, which is more accurate than most traditional methods.</span></p> <h4><b>Predicting Survival from Histology Slides</b></h4> <p><span style="font-weight: 400;">Convolutional neural networks have been particularly deep in analyzing histology slides and the prognosis of the life span of cancer patients. Digital histopathological images teach these models to understand features related to malignancy and patient survival. For instance, research has demonstrated that CNNs accurately evaluate the tumor microenvironment and estimate the overall survival rates of patients diagnosed with colorectal cancer. Because these models were trained using thousands of images, they can accurately capture the histology of primary tumors, including the stromal content and distribution of tumor cells, which are prognostic factors.</span></p> <p><span style="font-weight: 400;">Deep learning models can also help unravel the processes that lead to cancer progression, for instance, by identifying histological features that are indicative of poor survival. For example, AI models can study and rate basic things that are hard to measure with notations, such as microvascular proliferation, necrosis, and cellular heterogeneity. Not only does this automated analysis improve the accuracy of prognostic prediction but also helps in determining the kind of care that is appropriate for a specific patient.</span></p> <h4><b>Integrating Genomics with Histopathology</b></h4> <p><span style="font-weight: 400;">In other words, histology studies the tumor’s outer structure, while genomics studies how cancer works by looking at mutations, gene expression patterns, and other changes that make up a tumor’s features. Combining these two kinds of data with deep learning models can give a better picture of the disease.</span></p> <p><span style="font-weight: 400;">Researchers have established deep learning frameworks that fuse histological and genomic data to enhance diagnostic and prognostic strength. For example, models trained on whole-slide images and genomic data can predict patients’ outcomes with better accuracy than existing models. These types of multimodal models incorporate molecular changes such as mutation profiles, gene expression profiles, and CNAs alongside histopathology features to provide a comprehensive understanding of cancer.</span></p> <p><span style="font-weight: 400;">Molecular profiles and formalin-fixed paraffin-embedded tissue sections can find outcomes that are clinically important, like how often cancer comes back, how long people live, and how well they respond to treatment. This is because of deep learning. This method not only improves the accuracy of predictions but also helps figure out how the changes in the genome affect the tumor’s pathologic features.</span></p> <h4><b>Identifying Biomarkers and Predicting Treatment Response</b></h4> <p><span style="font-weight: 400;">Deep learning also plays a critical role in detecting biomarkers that can help in the determination of cancer treatment tests. The HDCM deep learning algorithm finds features in primary tumor images that are linked to genetic mutations, protein levels, and other factors that are important for treatment. The HDCM deep learning algorithm identifies features in primary tumor images that correlate with genetic mutations, protein levels, and other treatment-relevant factors. The algorithm makes observations in gliomas using MRI and histology images. Such models help in predicting the likelihood of occurrence of mutations such as IDH1, 1p/19q codeletion, and MGMT promoter. methylation. This information is crucial for developing effective treatment strategies. Likewise, using such deep learning techniques, it is possible to determine the response to immunotherapy in colorectal cancer, based on mismatch repair deficiencies and microsatellite instability.</span></p> <p><span style="font-weight: 400;">Deep learning models also have the potential to predict responses to targeted therapies as well as immunotherapies. Because AI models can figure out the chances of getting the best results from PD-1 blockade immunotherapy in cancers that don’t have enough mismatch repair, this is possible. This predictive capacity is especially beneficial to cancer treatment since it assists oncologists in choosing the most appropriate treatment methods for patients.</span></p> <p></div></div> <div style="background: #f7f7f7;border: 1px solid rgba(0, 0, 0, 0.07);"> <div style="padding: 30px;"><div class="Adblock-main"> <div class="Adblock-head"> <h2>Recent Publications on <b>“<a href="https://histology.blog/recent-publications/index/cancer diagnostics" target="_blank" rel="noopener" title="cancer diagnostics - yearwise publication list">cancer diagnostics</a>”</b></h2> </div> </div> <div class="pb-main"><div class="article-scroll"><div id="results_recent" class="results"></div></div><div class="keywordsdiv" style="margin: 0px 15px;margin-top:20px;"> <div style="text-align:center;"><b>Find publications on relevant topics</b> </div> <span class="gp-icon icon-tags"><svg viewBox="0 0 512 512" aria-hidden="true" xmlns="http://www.w3.org/2000/svg" width="1em" height="1em"><path d="M20 39.5c-8.836 0-16 7.163-16 16v176c0 4.243 1.686 8.313 4.687 11.314l224 224c6.248 6.248 16.378 6.248 22.626 0l176-176c6.244-6.244 6.25-16.364.013-22.615l-223.5-224A15.999 15.999 0 00196.5 39.5H20zm56 96c0-13.255 10.745-24 24-24s24 10.745 24 24-10.745 24-24 24-24-10.745-24-24z"></path><path d="M259.515 43.015c4.686-4.687 12.284-4.687 16.97 0l228 228c4.686 4.686 4.686 12.284 0 16.97l-180 180c-4.686 4.687-12.284 4.687-16.97 0-4.686-4.686-4.686-12.284 0-16.97L479.029 279.5 259.515 59.985c-4.686-4.686-4.686-12.284 0-16.97z"></path></svg></span> <span id="keyword-papers"></span> </div></div></div><div class="inside-article"> <style> .pb-main{ border: solid 1px #ccc; border-top: none; margin-bottom: 20px; padding-bottom: 25px; background:#fff; } .author-main { border: solid 1px #ccc; border-top: none; margin-bottom: 20px; padding-bottom: 25px; background:#fff; } .publication-block { padding: 10px; margin-bottom: 10px; background-color: #f9f9f9; text-align: left; background: #FFF; border-bottom: solid 1px #ccc; margin-left: 15px; margin-right: 15px; } .publication-block h3 { margin: 0 0 10px; color: #000!important; } .publication-block a { font-size: 16px !important; line-height: 1em; font-weight: 600; text-transform: none; color: #000; padding: 0px; } .publication-block a:hover{ color: #227cdc; text-decoration:underline; } .article-scroll { max-height: 445px; overflow-y: auto; overflow-x: hidden; } ::-webkit-scrollbar-track { -webkit-box-shadow: inset 0 0 6px rgba(0,0,0,0.3); background-color: #efefef; border-radius:30px; } ::-webkit-scrollbar { width: 6px; background-color: #efefef; border-radius:30px; } ::-webkit-scrollbar-thumb { background-color: #ababab; border-radius:30px; } .publication-block p { margin-bottom: .5em; font-size: 15px; color: #000; } h3 { font-size: 18px !important; margin-bottom: 20px; line-height: 1.2em; font-weight: 600; text-transform: none; } a { padding: 5px; color: #a71c49; } #keyword-papers{ margin-top: 20px; text-align: center; } </style> <script> function decodeString(str) { str = str.replace(/\\'/g, "'"); str = str.replace(/\\'/g, "'"); str = str.replace(/\\'/g, "'"); return str; } function displayResults_recent(papers) { var resultsContainer = document.getElementById('results_recent'); if (!papers || papers.length === 0) { resultsContainer.innerHTML = '<p>No recent publications found.</p>'; return; } papers.forEach(paper => { var publicationBlock = document.createElement('div'); publicationBlock.className = 'publication-block'; var title_de = decodeString(paper.title); var publicationHTML = ` <div style="margin-bottom: 10px;line-height: 24px;"><a href="${paper.url}" target="_blank" title="${title_de}">${title_de}</a></div> <p><strong>Issue Release:</strong> ${paper.publishedDate}</p> `; publicationBlock.innerHTML = publicationHTML; resultsContainer.appendChild(publicationBlock); }); } function displayKeywordPapers(keywords) { var resultsContainer = document.getElementById('keyword-papers'); resultsContainer.innerHTML = ''; if (!keywords || keywords.length === 0) { resultsContainer.innerHTML = '<p>No data found.</p>'; return; } var keywordHTML = ''; keywords.forEach((key, index) => { let key_replace = key.replace(/ /g, '-'); key_replace = key_replace.toLowerCase(); keywordHTML += `<a href="https://histology.blog/recent-publications/index/${key_replace}" target="_blank" title="${key} - publication list">${key}</a>`; if (index < keywords.length - 1) { keywordHTML += ', '; } }); resultsContainer.innerHTML = keywordHTML; } // Call the function with the PHP data var recent_papers = [ { "title": "A self-immobilizing near-infrared fluorogenic probe for in vivo imaging of fibroblast activation protein-\u03b1.", "url": "https:\/\/pubmed.ncbi.nlm.nih.gov\/38944939", "publishedDate": "2024" }, { "title": "A critical appraisal of the role of metabolomics in breast cancer research and diagnostics.", "url": "https:\/\/pubmed.ncbi.nlm.nih.gov\/38944408", "publishedDate": "2024" }, { "title": "From Genotype to Phenotype: Raman Spectroscopy and Machine Learning for Label-Free Single-Cell Analysis.", "url": "https:\/\/pubmed.ncbi.nlm.nih.gov\/38950145", "publishedDate": "2024" }, { "title": "Electrolyte-gated amorphous IGZO transistors with extended gates for prostate-specific antigen detection.", "url": "https:\/\/pubmed.ncbi.nlm.nih.gov\/38847194", "publishedDate": "2024" }, { "title": "A Kernelized Classification Approach for Cancer Recognition Using Markovian Analysis of DNA Structure Patterns as Feature Mining.", "url": "https:\/\/pubmed.ncbi.nlm.nih.gov\/38847942", "publishedDate": "2024" }, { "title": "Identifying miRNA as biomarker for breast cancer subtyping using association rule.", "url": "https:\/\/pubmed.ncbi.nlm.nih.gov\/38850957", "publishedDate": "2024" }, { "title": "Is Automatic Tumor Segmentation on Whole-Body F-FDG PET Images a Clinical Reality?", "url": "https:\/\/pubmed.ncbi.nlm.nih.gov\/38844359", "publishedDate": "2024" }, { "title": "Amonafide-based HO-responsive theranostic prodrugs: Exploring the correlation between HO level and anticancer efficacy.", "url": "https:\/\/pubmed.ncbi.nlm.nih.gov\/38878752", "publishedDate": "2024" }, { "title": "Assessment of Biological Damage Induced during Multidetector Computed Tomography (MDCT) Examination.", "url": "https:\/\/pubmed.ncbi.nlm.nih.gov\/38858307", "publishedDate": "2024" }, { "title": "Urinary PSA-ZINC biomarker outperforms standard of care in early detection of prostate cancer.", "url": "https:\/\/pubmed.ncbi.nlm.nih.gov\/38864687", "publishedDate": "2024" }, { "title": "Clinical application of targeted tumour sequencing tests for detecting ERBB2 amplification and optimizing anti-HER2 therapy in gastric cancer.", "url": "https:\/\/pubmed.ncbi.nlm.nih.gov\/38862927", "publishedDate": "2024" }, { "title": "CoHIT: a one-pot ultrasensitive ERA-CRISPR system for detecting multiple same-site indels.", "url": "https:\/\/pubmed.ncbi.nlm.nih.gov\/38866774", "publishedDate": "2024" }, { "title": "Efficacy of blood plasma spectroscopy for early liver cancer diagnostics in obese patients.", "url": "https:\/\/pubmed.ncbi.nlm.nih.gov\/38866366", "publishedDate": "2024" }, { "title": "Infectious complications in the paediatric immunocompromised host: a narrative review.", "url": "https:\/\/pubmed.ncbi.nlm.nih.gov\/38851426", "publishedDate": "2024" }, { "title": "Biocompatibility characterisation of CMOS-based Lab-on-Chip electrochemical sensors for in vitro cancer cell culture applications.", "url": "https:\/\/pubmed.ncbi.nlm.nih.gov\/38941688", "publishedDate": "2024" }, { "title": "HPV, HBV, and HIV-1 Viral Integration Site Mapping: A Streamlined Workflow from NGS to Genomic Insights of Carcinogenesis.", "url": "https:\/\/pubmed.ncbi.nlm.nih.gov\/38932267", "publishedDate": "2024" }, { "title": "Findings and Challenges in Replacing Traditional Uterine Cervical Cancer Diagnosis with Molecular Tools in Private Gynecological Practice in Mexico.", "url": "https:\/\/pubmed.ncbi.nlm.nih.gov\/38932179", "publishedDate": "2024" }, { "title": "Determinants of Chromatin Organization in Aging and Cancer-Emerging Opportunities for Epigenetic Therapies and AI Technology.", "url": "https:\/\/pubmed.ncbi.nlm.nih.gov\/38927646", "publishedDate": "2024" }, { "title": "Novel Semi-Nested Real-Time PCR Assay Leveraging Extendable Blocking Probes for Improved Methylation Analysis in Lung Cancer.", "url": "https:\/\/pubmed.ncbi.nlm.nih.gov\/38927132", "publishedDate": "2024" }, { "title": "Pan-cancer proteogenomics expands the landscape of therapeutic targets.", "url": "https:\/\/pubmed.ncbi.nlm.nih.gov\/38917788", "publishedDate": "2024" } ]; var keywordsArray = ["Deep learning","cancer diagnostics","histopathology","genomics","convolutional neural networks","predictive biomarkers","cancer prognosis","personalized medicine","AI in healthcare"]; displayResults_recent(recent_papers); displayKeywordPapers(keywordsArray); // function stripslashes(str) { // if (typeof str === 'string') { // return str.replace(/\/g, ''); // } // } </script></p> <h4><b>Enhancing Diagnostic Accuracy and Reducing Variability</b></h4> <p><span style="font-weight: 400;">The application of deep learning in cancer diagnostics addresses a critical challenge in pathology: it will help to reduce the problem of inter-observer variability. The main problem with traditional histopathological analysis is that it relies on the opinions of pathologists, which means that different observers can make different diagnoses and give different grades. Deep-learning tissue segmentation models set a new standard for tissue analysis by reducing variation and increasing the possibility of making a diagnosis.</span></p> <p><span style="font-weight: 400;">Pathologists find the use of wise diagnostic tools, which include several parameters such as tumor grading, mitosis detection, and quantification of histological features, tiresome. These tools not only save time but also reduce the likelihood of errors during sample diagnosis by conducting equally rigorous tests on all obtained samples.</span></p> <p><span style="font-weight: 400;">Furthermore, we can train deep learning models on specific histopathological features associated with different cancer subtypes to aid in precise classification and diagnosis. For example, scientists have taught CNNs to correctly identify different types of breast cancer from histological images. They can do this by guessing the status of hormonal receptors and other markers without having to do expensive molecular testing on the samples.</span></p> <h3><b>Challenges and Future Directions</b></h3> <p><span style="font-weight: 400;">However, there are some challenges in the implementation of deep learning in clinical practices, although the studies have produced promising results. The availability of large datasets, tagged and curated to prepare ideal models, poses a major challenge. These limitations, which include differences in staining, image quality, and even the slides used in different institutions, pose a significant challenge to models that should come with standardized protocols.</span></p> <p><span style="font-weight: 400;">Furthermore, the rationale behind deep learning models is difficult to understand due to their ‘black box’ characteristics, which makes clinical implementation difficult. Current work is in progress, to build explainable artificial intelligence systems, whereby clinicians can understand the way in which the predictions are being arrived at, increasing clinician trust in these models.</span></p> <p><span style="font-weight: 400;">Future deep-learning models will continue to use cancers diagnosed with histology, genomics, and other clinical data. </span><span style="font-weight: 400;">With these models, it is possible to obtain patient-individualized risk estimation, make the right decisions concerning treatment, and, as a result, achieve better outcomes.</span></p> <h3><b>Conclusion</b></h3> <p><span style="font-weight: 400;">Deep learning is revolutionizing cancer diagnostics and replacing traditional approaches with histopathology and genomics. From predicting if a patient is likely to survive or not beyond five years to the identification of patient subgroups, that may respond positively to treatment, such AI models are opening up new horizons in cancer care management. Future developments in these technologies promise to improve diagnostic accuracy, decrease inter-observer variability, and ultimately contribute to cancer fights and better patient care.</span></p> <p></p> <h3><b>References</b></h3> <ol> <li>Lakkis, J., Wang, D., Zhang, Y., Hu, G., Wang, K., Pan, H., Ungar, L., Reilly, M.P., Li, X. and Li, M., 2021. <a href="https://genome.cshlp.org/content/31/10/1753.short">A joint deep learning model enables simultaneous batch effect correction, denoising, and clustering in single-cell transcriptomics.</a> <i>Genome research</i>, <i>31</i>(10), pp.1753-1766.</li> <li>Kather, J.N., Krisam, J., Charoentong, P., Luedde, T., Herpel, E., Weis, C.A., Gaiser, T., Marx, A., Valous, N.A., Ferber, D. and Jansen, L., 2019. <a href="https://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1002730">Predicting survival from colorectal cancer histology slides using deep learning: A retrospective multicenter study.</a> <i>PLoS medicine</i>, <i>16</i>(1), p.e1002730.</li> <li>Chang, P., Grinband, J., Weinberg, B.D., Bardis, M., Khy, M., Cadena, G., Su, M.Y., Cha, S., Filippi, C.G., Bota, D. and Baldi, P., 2018. <a href="https://www.ajnr.org/content/39/7/1201.short">Deep-learning convolutional neural networks accurately classify genetic mutations in gliomas.</a> <i>American Journal of Neuroradiology</i>, <i>39</i>(7), pp.1201-1207.</li> <li>Chen, R.J., Lu, M.Y., Wang, J., Williamson, D.F., Rodig, S.J., Lindeman, N.I. and Mahmood, F., 2020. <a href="https://ieeexplore.ieee.org/abstract/document/9186053">Pathomic fusion: an integrated framework for fusing histopathology and genomic features for cancer diagnosis and prognosis.</a> <i>IEEE Transactions on Medical Imaging</i>, <i>41</i>(4), pp.757-770.</li> <li>Kather, J.N., Schulte, J., Grabsch, H.I., Loeffler, C., Muti, H., Dolezal, J., Srisuwananukorn, A., Agrawal, N., Kochanny, S., Stillfried, S.V. and Boor, P., 2019. <a href="https://www.biorxiv.org/content/10.1101/690206v1.abstract">Deep learning detects virus presence in cancer histology.</a> <i>BioRxiv</i>, p.690206.</li> <li>Mobadersany, P., Yousefi, S., Amgad, M., Gutman, D.A., Barnholtz-Sloan, J.S., Velázquez Vega, J.E., Brat, D.J. and Cooper, L.A., 2018. <a href="https://www.pnas.org/doi/abs/10.1073/pnas.1717139115">Predicting cancer outcomes from histology and genomics using convolutional networks.</a> <i>Proceedings of the National Academy of Sciences</i>, <i>115</i>(13), pp.E2970-E2979.</li> <li>Chen, K.H., Boettiger, A.N., Moffitt, J.R., Wang, S. and Zhuang, X., 2015. <a href="https://www.science.org/doi/full/10.1126/science.aaa6090">Spatially resolved, highly multiplexed RNA profiling in single cells.</a> <i>Science</i>, <i>348</i>(6233), p.aaa6090.</li> <li>Lee, J., Lee, J. and Kim, J.H., 2019. <a href="https://ar.iiarjournals.org/content/39/11/5963.short">Identification of matrix metalloproteinase 11 as a prognostic biomarker in pancreatic cancer.</a> <i>Anticancer Research</i>, <i>39</i>(11), pp.5963-5971.</li> </ol> <p></div></div> <div style="background: #f7f7f7;border: 1px solid rgba(0, 0, 0, 0.07);"> <div style="padding: 30px;"><div class="Adblock-main"> <div class="Adblock-head"> <h2>Top Experts on “<b style="color:#000;font-size:22px;">cancer diagnostics</b>“</h2> </div> </div><div class="author-main"><div id="results_author"></div><div style="text-align: center;"><a class="register-button" href="https://histology.blog/expert-search" target="_blank" rel="noopener">Find experts on any field</a></div></div><div class="inside-article" style="background: none;border: none;box-shadow: none;margin-top: -70px;"> <style> .author-block { padding: 15px; margin-bottom: 10px; text-align: left; font-size: 15px; line-height: 1.2; background: #FFF; border-bottom: solid 1px #ccc; margin-left: 15px; margin-right: 15px; } .author-block h3 { margin: 0 0 10px; color: #227cdc; } .author-block p { margin: 5px 0; } .author-b { display: flex; justify-content: space-between; flex-wrap: wrap; margin-bottom:10px; } .author-b .ainfo { flex: 1 1 30%; box-sizing: border-box; text-align: left; background: #dcdcdc; padding: 7px 14px; border-radius: 5px; margin-top: 3px; margin-right: 10px; } @media (max-width: 768px) { .author-b .ainfo { flex: 1 1 100%; margin: 10px 0; } } </style> <script> function displayResults_author(authors) { var resultsContainer = document.getElementById('results_author'); resultsContainer.innerHTML = ''; if (!authors || Object.keys(authors).length === 0) { resultsContainer.innerHTML = '<p>No authors found.</p>'; return; } Object.values(authors).slice(0, 10).forEach(author => { if (author.affiliation.length > 400) { return; } var authorBlock = document.createElement('div'); authorBlock.className = 'author-block'; var author_name=author.name; let key_replace = author_name.replace(/ /g, '-'); key_replace = key_replace.toLowerCase(); var authorHTML = ` <h3><a href="https://histology.blog/author/index/${key_replace}\/${author.aid}" target="_blank" title="${author.name}">${author.name}</a></h3> <div class="author-b"> <div class="ainfo"><strong>H-Index:</strong> ${author.hindex}</div> <div class="ainfo"><strong>Publication Count:</strong> ${author.paper_count}</div> <div class="ainfo"><strong>Citation Count:</strong> ${author.citation_count}</div> </div> <p><strong>Affiliation:</strong> ${author.affiliation}</p> `; authorBlock.innerHTML = authorHTML; resultsContainer.appendChild(authorBlock); }); } function displayKeywordAuthors(keywords) { var resultsContainer = document.getElementById('keyword-authors'); resultsContainer.innerHTML = ''; if (!keywords || keywords.length === 0) { resultsContainer.innerHTML = '<p>No data found.</p>'; return; } var keywordHTML = ''; keywords.forEach(key => { let key_replace = key.replace(/ /g, '-'); key_replace = key_replace.toLowerCase(); keywordHTML += `<a href="https://histology.blog/expert-search/index/${key_replace}" target="_blank" title="${key}">${key}</a>`; }); resultsContainer.innerHTML = keywordHTML; } // Call the function with the PHP data var authors_data = { "yuwwK4wBWBy50K-rEKuG": { "aid": "yuwwK4wBWBy50K-rEKuG", "name": "B. Wilson", "citation_count": 44573, "hindex": 96, "paper_count": 744, "affiliation": "Princess Margaret Cancer Centre\/University Health Network, Toronto, ON, Canada. ", "email": "brian.wilson@uhnresearch.ca", "slug_tail": "b-wilson" }, "QSTwK4wBWBy50K-rTXut": { "aid": "QSTwK4wBWBy50K-rTXut", "name": "E. Cuppen", "citation_count": 33884, "hindex": 87, "paper_count": 393, "affiliation": "Center for Molecular Medicine and Oncode Institute, University Medical Center Utrecht, Universiteitsweg 100, 3584 CG, Utrecht, The Netherlands. ", "email": "ecuppen@umcutrecht.nl", "slug_tail": "e-cuppen" }, "Da8lK4wBWBy50K-rdX_l": { "aid": "Da8lK4wBWBy50K-rdX_l", "name": "D. Kerr", "citation_count": 31628, "hindex": 81, "paper_count": 545, "affiliation": "Radcliffe Department of Medicine, University of Oxford, Oxford OX3 9DS, United Kingdom; Oxford-Sichuan Gastrointestinal Cancer Centre, University of Oxford, Oxford OX3 9DS, United Kingdom. ", "email": "david.kerr@ndcls.ox.ac.uk", "slug_tail": "d-kerr" }, "iUMNK4wBWBy50K-rn32w": { "aid": "iUMNK4wBWBy50K-rn32w", "name": "M. Greene", "citation_count": 22155, "hindex": 77, "paper_count": 490, "affiliation": "Department of Pathology and Lab Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104-6082, USA. ", "email": "greenemarkirwin@gmail.com", "slug_tail": "m-greene" }, "yzR2K4wBWBy50K-ralzu": { "aid": "yzR2K4wBWBy50K-ralzu", "name": "J. Jassem", "citation_count": 40527, "hindex": 74, "paper_count": 814, "affiliation": "Medical University of Gda\u0144sk, Gda\u0144sk, Poland. ", "email": "jjassem@gumed.edu.pl", "slug_tail": "j-jassem" }, "yX9OK4wBWBy50K-rMgCZ": { "aid": "yX9OK4wBWBy50K-rMgCZ", "name": "A. Hoischen", "citation_count": 18442, "hindex": 71, "paper_count": 294, "affiliation": "Department of Human Genetics, Radboud University Medical Center, Nijmegen, The Netherlands. ", "email": "alexander.hoischen@radboudumc.nl", "slug_tail": "a-hoischen" }, "mP-uK4wBWBy50K-rQVWJ": { "aid": "mP-uK4wBWBy50K-rQVWJ", "name": "B. Ylstra", "citation_count": 17503, "hindex": 63, "paper_count": 375, "affiliation": "Department of Pathology, Cancer Center Amsterdam, Amsterdam University Medical Center, Location Vrije Universiteit Medical Center Amsterdam, Amsterdam, the Netherlands. ", "email": "b.ylstra@amsterdamumc.nl", "slug_tail": "b-ylstra" }, "XmLkKowBWBy50K-rLGFU": { "aid": "XmLkKowBWBy50K-rLGFU", "name": "D. Parkin", "citation_count": 73371, "hindex": 61, "paper_count": 206, "affiliation": "Nuffield Department of Population Health, University of Oxford, UK. ", "email": "max.parkin@ndph.ox.ac.uk", "slug_tail": "d-parkin" }, "Kn6JK4wBWBy50K-rvvIr": { "aid": "Kn6JK4wBWBy50K-rvvIr", "name": "U. Landegren", "citation_count": 17018, "hindex": 57, "paper_count": 298, "affiliation": "Department of Immunology, Genetics and Pathology, Science for Life Laboratory, Uppsala University, Uppsala, Sweden. ", "email": "ulf.landegren@igp.uu.se", "slug_tail": "u-landegren" }, "TV7EK4wBWBy50K-rVi8X": { "aid": "TV7EK4wBWBy50K-rVi8X", "name": "M. Babjuk", "citation_count": 16268, "hindex": 57, "paper_count": 384, "affiliation": "Department of Urology, 2nd Faculty of Medicine, Hospital Motol, Charles University, Prague, Czech Republic; Department of Urology, Medical University of Vienna, Vienna, Austria. ", "email": "Marek.Babjuk@fnmotol.cz", "slug_tail": "m-babjuk" }, "j8cpK4wBWBy50K-rpULL": { "aid": "j8cpK4wBWBy50K-rpULL", "name": "T. Haystead", "citation_count": 11017, "hindex": 53, "paper_count": 169, "affiliation": "Department of Pharmacology and Cancer Biology, Duke University School of Medicine, Durham, North Carolina 27710 ", "email": "Timothy.haystead@duke.edu", "slug_tail": "t-haystead" }, "RTf2K4wBWBy50K-rtlEV": { "aid": "RTf2K4wBWBy50K-rtlEV", "name": "C. Gratzke", "citation_count": 10881, "hindex": 53, "paper_count": 564, "affiliation": "Department of Urology, Albert-Ludwigs University, Freiburg, Germany. ", "email": "christian.gratzke@uniklinik-freiburg.de", "slug_tail": "c-gratzke" }, "sGZIK4wBWBy50K-rbBaR": { "aid": "sGZIK4wBWBy50K-rbBaR", "name": "A. Torkamani", "citation_count": 10385, "hindex": 50, "paper_count": 175, "affiliation": "The Scripps Translational Science Institute, The Scripps Research Institute, 3344 North Torrey Pines Court Suite 300, La Jolla, CA, 92037, USA. ", "email": "atorkama@scripps.edu", "slug_tail": "a-torkamani" }, "7T68K4wBWBy50K-r6uMP": { "aid": "7T68K4wBWBy50K-r6uMP", "name": "Jiashu Sun", "citation_count": 6504, "hindex": 50, "paper_count": 121, "affiliation": "CAS Key Laboratory of Standardization and Measurement for Nanotechnology, CAS Center for Excellence in Nanoscience, National Center for Nanoscience and Technology, Beijing, China. ", "email": "sunjs@nanoctr.cn", "slug_tail": "jiashu-sun" }, "2ffQKowBWBy50K-rC51w": { "aid": "2ffQKowBWBy50K-rC51w", "name": "P. Kapranov", "citation_count": 32169, "hindex": 49, "paper_count": 161, "affiliation": "Institute of Genomics, School of Biomedical Sciences, Huaqiao University, 668 Jimei Road, Xiamen, 361021, China. ", "email": "philippk08@hotmail.com", "slug_tail": "p-kapranov" }, "-cWcK4wBWBy50K-rf6g2": { "aid": "-cWcK4wBWBy50K-rf6g2", "name": "N. Rosenfeld", "citation_count": 19666, "hindex": 48, "paper_count": 139, "affiliation": "Inivata, Cambridge CB22 3FH, UK; Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge CB2 0RE, UK; Cancer Research UK Cambridge Centre, Cambridge CB2 0RE, UK. ", "email": "nitzan.rosenfeld@cruk.cam.ac.uk", "slug_tail": "n-rosenfeld" }, "HPXmK4wBWBy50K-rJxqE": { "aid": "HPXmK4wBWBy50K-rJxqE", "name": "Xuemei Wang", "citation_count": 8070, "hindex": 45, "paper_count": 333, "affiliation": "State Key Laboratory of Bioelectronics, National Demonstration Center for Experimental Biomedical Engineering Education, School of Biological Science and Medical Engineering, Southeast University, Nanjing 210096, China. ", "email": "xuewang@seu.edu.cn", "slug_tail": "xuemei-wang" }, "sUvAK4wBWBy50K-rR1k3": { "aid": "sUvAK4wBWBy50K-rR1k3", "name": "H. Danielsen", "citation_count": 5644, "hindex": 45, "paper_count": 169, "affiliation": "Institute for Cancer Genetics and Informatics, Oslo University Hospital, NO-0424, Oslo, Norway. ", "email": "hdaniels@labmed.uio.no", "slug_tail": "h-danielsen" }, "1j_4K4wBWBy50K-re8J_": { "aid": "1j_4K4wBWBy50K-re8J_", "name": "Wei R. Chen", "citation_count": 5721, "hindex": 45, "paper_count": 320, "affiliation": "Biophotonics Research Laboratory, Center for Interdisciplinary Biomedical Education and Research, College of Mathematics and Science, University of Central Oklahoma, Edmond, OH 73034, USA. ", "email": "wchen@uco.edu", "slug_tail": "wei-r-chen" }, "zxLVKowBWBy50K-rywST": { "aid": "zxLVKowBWBy50K-rywST", "name": "C. Balleyguier", "citation_count": 7284, "hindex": 44, "paper_count": 247, "affiliation": "Imaging Department, Gustave Roussy, 114 rue Edouard Vaillant, 94800, Villejuif, France. ", "email": "corinne.balleyguier@gustaveroussy.fr", "slug_tail": "c-balleyguier" }, "zwGuK4wBWBy50K-rpL_0": { "aid": "zwGuK4wBWBy50K-rpL_0", "name": "M. Danquah", "citation_count": 12169, "hindex": 44, "paper_count": 262, "affiliation": "Department of Chemical Engineering, University of Tennessee, Chattanooga, TN 37403, United States. ", "email": "michael-danquah@utc.edu", "slug_tail": "m-danquah" }, "IDY-K4wBWBy50K-rL9I_": { "aid": "IDY-K4wBWBy50K-rL9I_", "name": "D. Clevert", "citation_count": 7883, "hindex": 43, "paper_count": 317, "affiliation": "Klinik und Poliklinik f\u00fcr Radiologie, Interdisziplin\u00e4res Ultraschallzentrum, Klinikum der Ludwig-Maximilians-Universit\u00e4t M\u00fcnchen, Campus Gro\u00dfhadern, Marchioninistra\u00dfe\u00a015, 81377, M\u00fcnchen, Deutschland. ", "email": "Dirk.Clevert@med.uni-muenchen.de", "slug_tail": "d-clevert" }, "5bXXK4wBWBy50K-rsVlq": { "aid": "5bXXK4wBWBy50K-rsVlq", "name": "R. Barr", "citation_count": 8448, "hindex": 42, "paper_count": 203, "affiliation": "Northeastern Ohio Medical University, Southwoods Imaging, 7623 Market Street, Youngstown, OH 44512, USA. ", "email": "rgbarr@zoominternet.net", "slug_tail": "r-barr" }, "8OZlK4wBWBy50K-rg17m": { "aid": "8OZlK4wBWBy50K-rg17m", "name": "G. Salomon", "citation_count": 6596, "hindex": 42, "paper_count": 298, "affiliation": "Martini Clinic, Prostate Cancer Centre, University Medical Centre Eppendorf, Hamburg, Germany. ", "email": "gsalomon@uke.uni-hamburg.de", "slug_tail": "g-salomon" }, "DsqdK4wBWBy50K-rXjd2": { "aid": "DsqdK4wBWBy50K-rXjd2", "name": "M. Minunni", "citation_count": 6776, "hindex": 41, "paper_count": 185, "affiliation": "Department of Chemistry \"Ugo Schiff\", University of Florence, via della Lastruccia 3\u207b13, Sesto Fiorentino, 50019 Firenze, Italy. ", "email": "maria.minunni@unifi.it", "slug_tail": "m-minunni" }, "XBA3K4wBWBy50K-rlYgu": { "aid": "XBA3K4wBWBy50K-rlYgu", "name": "C. Frochot", "citation_count": 6469, "hindex": 41, "paper_count": 231, "affiliation": "Universit\u00e9 de Lorraine, CNRS, LRGP, F-54000 Nancy, France. ", "email": "celine.frochot@univ-lorraine.fr", "slug_tail": "c-frochot" }, "QH_oKowBWBy50K-r6qsY": { "aid": "QH_oKowBWBy50K-r6qsY", "name": "H. Dubbink", "citation_count": 5676, "hindex": 40, "paper_count": 146, "affiliation": "Department of Pathology, Erasmus MC, University Medical Centre Rotterdam, the Netherlands. ", "email": "h.dubbink@erasmusmc.nl", "slug_tail": "h-dubbink" }, "e0vgKowBWBy50K-reDxD": { "aid": "e0vgKowBWBy50K-reDxD", "name": "Hui Jiang", "citation_count": 5974, "hindex": 40, "paper_count": 229, "affiliation": "State Key Laboratory of Bioelectronics (Chien-Shiung Wu Lab), School of Biological Science and Medical Engineering, Southeast University, Nanjing 210096, China. ", "email": "xuewang@seu.edu.cn", "slug_tail": "hui-jiang" }, "Pt6lK4wBWBy50K-rDuiJ": { "aid": "Pt6lK4wBWBy50K-rDuiJ", "name": "J. Hehir-Kwa", "citation_count": 6030, "hindex": 40, "paper_count": 98, "affiliation": "Princess M\u00e1xima Center for Pediatric Oncology, Utrecht, The Netherlands. ", "email": "J.Y.HehirKwa@prinsesmaximacentrum.nl", "slug_tail": "j-hehir-kwa" }, "ZHQWK4wBWBy50K-rkXlQ": { "aid": "ZHQWK4wBWBy50K-rkXlQ", "name": "P. Mcgale", "citation_count": 40423, "hindex": 39, "paper_count": 99, "affiliation": "University of Oxford, Nuffield Department of Population Health, Oxford, UK. ", "email": "paul.mcgale@ndph.ox.ac.uk", "slug_tail": "p-mcgale" }, "kjK5K4wBWBy50K-rPz0n": { "aid": "kjK5K4wBWBy50K-rPz0n", "name": "S. Done", "citation_count": 4590, "hindex": 39, "paper_count": 160, "affiliation": "Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Canada. ", "email": "susan.done@uhn.ca", "slug_tail": "s-done" }, "kcudK4wBWBy50K-rpZur": { "aid": "kcudK4wBWBy50K-rpZur", "name": "T. Herrmann", "citation_count": 4268, "hindex": 39, "paper_count": 195, "affiliation": "Department of Urology, Spital Thurgau AG (STGAG), Pfaffenholzstra\u00dfe4, 8501, Frauenfeld, Switzerland. ", "email": "thomas.herrmann@stgag.ch", "slug_tail": "t-herrmann" }, "ruTiK4wBWBy50K-rimtp": { "aid": "ruTiK4wBWBy50K-rimtp", "name": "M. Suar", "citation_count": 5130, "hindex": 38, "paper_count": 207, "affiliation": "School of Biotechnology, KIIT University, Bhubaneswar, Odisha, India. ", "email": "msuar@kiitbiotech.ac.in", "slug_tail": "m-suar" }, "ywywK4wBWBy50K-rXCJU": { "aid": "ywywK4wBWBy50K-rXCJU", "name": "Feifan Zhou", "citation_count": 4447, "hindex": 35, "paper_count": 149, "affiliation": "Biophotonics Research Laboratory, Center for Interdisciplinary Biomedical Education and Research, College of Mathematics and Science, University of Central Oklahoma, Edmond, OK, USA. ", "email": "zhouff@szu.edu.cn", "slug_tail": "feifan-zhou" }, "VV8SK4wBWBy50K-rZy2K": { "aid": "VV8SK4wBWBy50K-rZy2K", "name": "J. Vaidya", "citation_count": 7500, "hindex": 35, "paper_count": 347, "affiliation": "Division of Surgery and Interventional Science, University College London, London, UK. ", "email": "jayantvaidya@gmail.com", "slug_tail": "j-vaidya" }, "FhbXKowBWBy50K-rIdRW": { "aid": "FhbXKowBWBy50K-rIdRW", "name": "S. Cannistraro", "citation_count": 4655, "hindex": 34, "paper_count": 231, "affiliation": "Biophysics and Nanoscience Centre, DEB, Universit\u00e0 della Tuscia, Viterbo, Italy. ", "email": "cannistr@unitus.it", "slug_tail": "s-cannistraro" }, "kobqKowBWBy50K-rFn9o": { "aid": "kobqKowBWBy50K-rFn9o", "name": "C. C. Landry", "citation_count": 2588, "hindex": 32, "paper_count": 78, "affiliation": "Department of Chemistry, University of Vermont, 82 University Place, Burlington, VT 05405, USA. ", "email": "Christopher.Landry@uvm.edu", "slug_tail": "c-c-landry" }, "TisIK4wBWBy50K-rzzJH": { "aid": "TisIK4wBWBy50K-rzzJH", "name": "R. Shahzad", "citation_count": 3236, "hindex": 32, "paper_count": 80, "affiliation": "Department of Horticulture, The University of Haripur, Haripur, 22620, Khyber Pakhtunkhwa, Pakistan. ", "email": "raheemshehzad@ymail.com", "slug_tail": "r-shahzad" }, "O8tdK4wBWBy50K-r7DsG": { "aid": "O8tdK4wBWBy50K-r7DsG", "name": "V. Barzda", "citation_count": 2811, "hindex": 31, "paper_count": 178, "affiliation": "University of Toronto, Department of Physics, Toronto, M5S 1A7, Canada. ", "email": "virgis.barzda@utoronto.ca", "slug_tail": "v-barzda" }, "rBDVKowBWBy50K-rmc_x": { "aid": "rBDVKowBWBy50K-rmc_x", "name": "I. Roeder", "citation_count": 3075, "hindex": 31, "paper_count": 125, "affiliation": "Carl Gustav Carus Faculty of Medicine, Institute for Medical Informatics and Biometry, TU Dresden, Dresden, Saxony, Germany. ", "email": "ingo.roeder@tu-dresden.de", "slug_tail": "i-roeder" }, "Q5-SK4wBWBy50K-rJLOg": { "aid": "Q5-SK4wBWBy50K-rJLOg", "name": "A. Bizzarri", "citation_count": 2968, "hindex": 31, "paper_count": 142, "affiliation": "Department of Environmental and Biological Sciences, University of Tuscia, Viterbo, 01100, Italy. ", "email": "bizzarri@unitus.it", "slug_tail": "a-bizzarri" }, "36TwKowBWBy50K-rHeiC": { "aid": "36TwKowBWBy50K-rHeiC", "name": "S. Schott", "citation_count": 3486, "hindex": 31, "paper_count": 142, "affiliation": "Department of Gynecology and Obstetrics, University Hospital of Heidelberg, 69120 Heidelberg, Germany. ", "email": "sarah.schott@med.uni-heidelberg.de", "slug_tail": "s-schott" }, "G2fFK4wBWBy50K-r-iJ3": { "aid": "G2fFK4wBWBy50K-r-iJ3", "name": "P. Roepman", "citation_count": 8031, "hindex": 30, "paper_count": 115, "affiliation": "Hartwig Medical Foundation, Amsterdam, the Netherlands. ", "email": "p.roepman@hartwigmedicalfoundation.nl", "slug_tail": "p-roepman" }, "8JggK4wBWBy50K-rQZtp": { "aid": "8JggK4wBWBy50K-rQZtp", "name": "K. Venkatakrishnan", "citation_count": 3057, "hindex": 30, "paper_count": 211, "affiliation": "Ultrashort Laser Nano Manufacturing Research Facility, Department of Mechanical and Industrial Engineering, Ryerson University, 350 Victoria Street, Toronto, ON, M5B 2K3, Canada; Keenan Research Center, St. Michael's Hospital, 209 Victoria Street, Toronto, Ontario, M5B 1T8, Canada. ", "email": "venkat@ryerson.ca", "slug_tail": "k-venkatakrishnan" }, "d6UiK4wBWBy50K-r9JH-": { "aid": "d6UiK4wBWBy50K-r9JH-", "name": "K. Belkic", "citation_count": 3957, "hindex": 30, "paper_count": 171, "affiliation": "Department of Oncology-Pathology, Karolinska Institute, Stockholm, Sweden. ", "email": "Karen.Belkic@ki.se", "slug_tail": "k-belkic" }, "KUUNK4wBWBy50K-r7TMF": { "aid": "KUUNK4wBWBy50K-r7TMF", "name": "J. Heil", "citation_count": 2448, "hindex": 30, "paper_count": 122, "affiliation": "Department of Gynecology and Obstetrics, Heidelberg University Hospital, Im Neuenheimer Feld 440, 69120, Heidelberg, Germany. ", "email": "joerg.heil@med.uni-heidelberg.de", "slug_tail": "j-heil" }, "8RbtK4wBWBy50K-rtypH": { "aid": "8RbtK4wBWBy50K-rtypH", "name": "P. Kemmeren", "citation_count": 4766, "hindex": 29, "paper_count": 73, "affiliation": "Princess M\u00e1xima Center for Pediatric Oncology, Heidelberglaan 25, 3584 CG, Utrecht, The Netherlands. ", "email": "P.Kemmeren@prinsesmaximacentrum.nl", "slug_tail": "p-kemmeren" }, "MHiIK4wBWBy50K-rjrFi": { "aid": "MHiIK4wBWBy50K-rjrFi", "name": "C. Nativi", "citation_count": 3585, "hindex": 29, "paper_count": 302, "affiliation": "Department of Chemistry, University of Florence, via della Lastruccia, 3-13, I-50119 Sesto F. no (FI), Italy. ", "email": "cristina.nativi@unifi.it", "slug_tail": "c-nativi" }, "RzYLK4wBWBy50K-rE3-6": { "aid": "RzYLK4wBWBy50K-rE3-6", "name": "Chao Liu", "citation_count": 3231, "hindex": 29, "paper_count": 55, "affiliation": "Beijing Engineering Research Center for BioNanotechnology, CAS Key Laboratory of Standardization and Measurement for Nanotechnology, CAS Center for Excellence in Nanoscience, National Center for Nanoscience and Technology, Beijing, China. ", "email": "liuc@nanoctr.cn", "slug_tail": "chao-liu" }, "AQ9tK4wBWBy50K-rhqFH": { "aid": "AQ9tK4wBWBy50K-rhqFH", "name": "P. Grodzinski", "citation_count": 5572, "hindex": 29, "paper_count": 134, "affiliation": "Nanodelivery Systems and Devices Branch (NSDB), Cancer Imaging Program, Division of Cancer Treatment and Diagnosis, National Cancer Institute, United States of America. ", "email": "grodzinp@mail.nih.gov", "slug_tail": "p-grodzinski" } }; //console.log(authors_data); displayResults_author(authors_data); var keywordsArray = ["Deep learning","cancer diagnostics","histopathology","genomics","convolutional neural networks","predictive biomarkers","cancer prognosis","personalized medicine","AI in healthcare"]; displayKeywordAuthors(keywordsArray); </script></p> </div> <footer class="entry-meta" aria-label="Entry meta"> <span class="cat-links"><span class="gp-icon icon-categories"><svg viewBox="0 0 512 512" aria-hidden="true" xmlns="http://www.w3.org/2000/svg" width="1em" height="1em"><path d="M0 112c0-26.51 21.49-48 48-48h110.014a48 48 0 0143.592 27.907l12.349 26.791A16 16 0 00228.486 128H464c26.51 0 48 21.49 48 48v224c0 26.51-21.49 48-48 48H48c-26.51 0-48-21.49-48-48V112z" /></svg></span><span class="screen-reader-text">Categories </span><a href="https://histology.blog/archive/category/cancer-diagnostics/" rel="category tag">Cancer Diagnostics</a></span> <span class="tags-links"><span class="gp-icon icon-tags"><svg viewBox="0 0 512 512" aria-hidden="true" xmlns="http://www.w3.org/2000/svg" width="1em" height="1em"><path d="M20 39.5c-8.836 0-16 7.163-16 16v176c0 4.243 1.686 8.313 4.687 11.314l224 224c6.248 6.248 16.378 6.248 22.626 0l176-176c6.244-6.244 6.25-16.364.013-22.615l-223.5-224A15.999 15.999 0 00196.5 39.5H20zm56 96c0-13.255 10.745-24 24-24s24 10.745 24 24-10.745 24-24 24-24-10.745-24-24z"/><path d="M259.515 43.015c4.686-4.687 12.284-4.687 16.97 0l228 228c4.686 4.686 4.686 12.284 0 16.97l-180 180c-4.686 4.687-12.284 4.687-16.97 0-4.686-4.686-4.686-12.284 0-16.97L479.029 279.5 259.515 59.985c-4.686-4.686-4.686-12.284 0-16.97z" /></svg></span><span class="screen-reader-text">Tags </span><a href="https://histology.blog/archive/tag/ai-in-healthcare/" rel="tag">AI in healthcare</a>, <a href="https://histology.blog/archive/tag/cancer-diagnostics/" rel="tag">cancer diagnostics</a>, <a href="https://histology.blog/archive/tag/cancer-prognosis/" rel="tag">cancer prognosis</a>, <a href="https://histology.blog/archive/tag/convolutional-neural-networks/" rel="tag">convolutional neural networks</a>, <a href="https://histology.blog/archive/tag/deep-learning/" rel="tag">Deep learning</a>, <a href="https://histology.blog/archive/tag/genomics/" rel="tag">genomics</a>, <a href="https://histology.blog/archive/tag/histopathology/" rel="tag">histopathology</a>, <a href="https://histology.blog/archive/tag/personalized-medicine/" rel="tag">personalized medicine</a>, <a href="https://histology.blog/archive/tag/predictive-biomarkers/" rel="tag">predictive biomarkers</a></span> <nav id="nav-below" class="post-navigation" aria-label="Posts"> <div class="nav-next"><span class="gp-icon icon-arrow-right"><svg viewBox="0 0 192 512" aria-hidden="true" xmlns="http://www.w3.org/2000/svg" width="1em" height="1em" fill-rule="evenodd" clip-rule="evenodd" stroke-linejoin="round" stroke-miterlimit="1.414"><path d="M178.425 256.001c0 2.266-1.133 4.815-2.832 6.515L43.599 394.509c-1.7 1.7-4.248 2.833-6.514 2.833s-4.816-1.133-6.515-2.833l-14.163-14.162c-1.699-1.7-2.832-3.966-2.832-6.515 0-2.266 1.133-4.815 2.832-6.515l111.317-111.316L16.407 144.685c-1.699-1.7-2.832-4.249-2.832-6.515s1.133-4.815 2.832-6.515l14.163-14.162c1.7-1.7 4.249-2.833 6.515-2.833s4.815 1.133 6.514 2.833l131.994 131.993c1.7 1.7 2.832 4.249 2.832 6.515z" fill-rule="nonzero" /></svg></span><span class="next"><a href="https://histology.blog/archive/3d-tissue-environments/innovative-approaches-to-mapping-gene-expression-in-3d-tissue-environments/" rel="next">Innovative Approaches to Mapping Gene Expression in 3D Tissue Environments</a></span></div> </nav> </footer> </div> </article> </main> </div> <div class="widget-area sidebar is-right-sidebar" id="right-sidebar"> <div class="inside-right-sidebar"> <aside id="block-2" class="widget inner-padding widget_block widget_search"><form role="search" method="get" action="https://histology.blog/archive/" class="wp-block-search__button-outside wp-block-search__text-button wp-block-search" ><label class="wp-block-search__label" for="wp-block-search__input-1" >Search</label><div class="wp-block-search__inside-wrapper " ><input class="wp-block-search__input" id="wp-block-search__input-1" placeholder="" value="" type="search" name="s" required /><button aria-label="Search" class="wp-block-search__button wp-element-button" type="submit" >Search</button></div></form></aside><aside id="block-3" class="widget inner-padding widget_block"><div class="wp-block-group"><div class="wp-block-group__inner-container is-layout-flow wp-block-group-is-layout-flow"><h2 class="wp-block-heading">Recent Posts</h2><ul class="wp-block-latest-posts__list wp-block-latest-posts"><li><a class="wp-block-latest-posts__post-title" href="https://histology.blog/archive/skin-homeostasis/gap-junctions-in-the-epidermis-understanding-their-role-in-skin-homeostasis-and-disease/">Gap Junctions in the Epidermis: Understanding Their Role in Skin Homeostasis and Disease</a></li> <li><a class="wp-block-latest-posts__post-title" href="https://histology.blog/archive/3d-tissue-environments/innovative-approaches-to-mapping-gene-expression-in-3d-tissue-environments/">Innovative Approaches to Mapping Gene Expression in 3D Tissue Environments</a></li> <li><a class="wp-block-latest-posts__post-title" href="https://histology.blog/archive/cancer-diagnostics/deep-learning-in-cancer-diagnostics-predicting-outcomes-from-histology-and-genomics/">Deep Learning in Cancer Diagnostics: Predicting Outcomes from Histology and Genomics</a></li> </ul></div></div></aside><aside id="block-4" class="widget inner-padding widget_block"><div class="wp-block-group"><div class="wp-block-group__inner-container is-layout-flow wp-block-group-is-layout-flow"><h2 class="wp-block-heading">Recent Comments</h2><div class="no-comments wp-block-latest-comments">No comments to show.</div></div></div></aside> </div> </div> </div> </div> <div class="site-footer footer-bar-active footer-bar-align-right"> <footer class="site-info" aria-label="Site" itemtype="https://schema.org/WPFooter" itemscope> <div class="inside-site-info grid-container"> <div class="footer-bar"> <aside id="nav_menu-2" class="widget inner-padding widget_nav_menu"><div class="menu-footer-menu-container"><ul id="menu-footer-menu" class="menu"><li id="menu-item-34" class="menu-item menu-item-type-post_type menu-item-object-page menu-item-34"><a href="https://histology.blog/archive/privacy-policy/">Privacy Policy</a></li> <li id="menu-item-33" class="menu-item menu-item-type-post_type menu-item-object-page menu-item-33"><a href="https://histology.blog/archive/disclaimer/">Disclaimer</a></li> <li id="menu-item-32" class="menu-item menu-item-type-post_type menu-item-object-page menu-item-32"><a href="https://histology.blog/archive/terms-and-conditions/">Terms and Conditions</a></li> <li id="menu-item-31" class="menu-item menu-item-type-post_type menu-item-object-page menu-item-31"><a href="https://histology.blog/archive/contact-us/">Contact us</a></li> <li id="menu-item-30" class="menu-item menu-item-type-post_type menu-item-object-page menu-item-30"><a href="https://histology.blog/archive/about-us/">About us</a></li> </ul></div></aside> </div> <div class="copyright-bar"> © 2024 Histology </div> </div> </footer> </div> <script id="generate-a11y">!function(){"use strict";if("querySelector"in document&&"addEventListener"in window){var e=document.body;e.addEventListener("mousedown",function(){e.classList.add("using-mouse")}),e.addEventListener("keydown",function(){e.classList.remove("using-mouse")})}}();</script> <div class="gp-modal gp-search-modal" id="gp-search"> <div class="gp-modal__overlay" tabindex="-1" data-gpmodal-close> <div class="gp-modal__container"> <form role="search" method="get" class="search-modal-form" action="https://histology.blog/archive/"> <label for="search-modal-input" class="screen-reader-text">Search for:</label> <div class="search-modal-fields"> <input id="search-modal-input" type="search" class="search-field" placeholder="Search …" value="" name="s" /> <button aria-label="Search"><span class="gp-icon icon-search"><svg viewBox="0 0 512 512" aria-hidden="true" xmlns="http://www.w3.org/2000/svg" width="1em" height="1em"><path fill-rule="evenodd" clip-rule="evenodd" d="M208 48c-88.366 0-160 71.634-160 160s71.634 160 160 160 160-71.634 160-160S296.366 48 208 48zM0 208C0 93.125 93.125 0 208 0s208 93.125 208 208c0 48.741-16.765 93.566-44.843 129.024l133.826 134.018c9.366 9.379 9.355 24.575-.025 33.941-9.379 9.366-24.575 9.355-33.941-.025L337.238 370.987C301.747 399.167 256.839 416 208 416 93.125 416 0 322.875 0 208z" /></svg></span></button> </div> </form> </div> </div> </div> <script src="https://histology.blog/archive/wp-content/plugins/gp-premium/menu-plus/functions/js/sticky.min.js?ver=2.4.1" id="generate-sticky-js"></script> <!--[if lte IE 11]> <script src="https://histology.blog/archive/wp-content/themes/generatepress/assets/js/classList.min.js?ver=3.4.0" id="generate-classlist-js"></script> <![endif]--> <script id="generate-menu-js-extra"> var generatepressMenu = {"toggleOpenedSubMenus":"1","openSubMenuLabel":"Open Sub-Menu","closeSubMenuLabel":"Close Sub-Menu"}; </script> <script src="https://histology.blog/archive/wp-content/themes/generatepress/assets/js/menu.min.js?ver=3.4.0" id="generate-menu-js"></script> <script src="https://histology.blog/archive/wp-content/themes/generatepress/assets/dist/modal.js?ver=3.4.0" id="generate-modal-js"></script> </body> </html>