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Gumbs, covering new developments in artificial intelligence surgeries such as general surgery, oncology, urology, weight loss, colorectal surgery, trauma surgery, breast surgery, transplant surgery, orthopedics, gynecology, vascular surgery, cardiothoracic surgery, neurosurgery, plastic surgery, otorhinolaryngology, hepatobiliary surgery, digestive surgery, etc."><meta data-n-head="ssr" name="keywords" content=""><meta data-n-head="ssr" name="twitter:title" content="Artificial Intelligence Surgery - OAE Publishing Inc."><meta data-n-head="ssr" name="twitter:type" content="OAE Publishing Inc."><meta data-n-head="ssr" name="twitter:description" content="Artificial Intelligence Surgery is a peer-reviewed journal led by Editor-in-Chief Andrew A. Gumbs, covering new developments in artificial intelligence surgeries such as general surgery, oncology, urology, weight loss, colorectal surgery, trauma surgery, breast surgery, transplant surgery, orthopedics, gynecology, vascular surgery, cardiothoracic surgery, neurosurgery, plastic surgery, otorhinolaryngology, hepatobiliary surgery, digestive surgery, etc."><meta data-n-head="ssr" property="og:url" content="/ais"><meta data-n-head="ssr" property="og:type" content="OAE Publishing Inc."><meta data-n-head="ssr" property="og:site_name" content="Artificial Intelligence Surgery"><meta data-n-head="ssr" property="og:title" content="Artificial Intelligence Surgery"><title>Artificial Intelligence Surgery - OAE Publishing Inc.</title><link data-n-head="ssr" rel="icon" type="image/x-icon" href="/favicon.ico"><link data-n-head="ssr" rel="canonical" href="https://www.oaepublish.com/ais"><script data-n-head="ssr" src="https://accounts.google.com/gsi/client" async></script><script data-n-head="ssr" src="https://g.oaes.cc/oae/dist/relijs.js" async></script><script data-n-head="ssr" src="https://www.googletagmanager.com/gtag/js?id=G-FM6KBJGRBV" async></script><link rel="preload" href="https://g.oaes.cc/oae/nuxt/eaa7ad8.js" as="script"><link rel="preload" href="https://g.oaes.cc/oae/nuxt/448d4b2.js" as="script"><link rel="preload" href="https://g.oaes.cc/oae/nuxt/css/8176b15.css" as="style"><link rel="preload" href="https://g.oaes.cc/oae/nuxt/66c63bd.js" as="script"><link rel="preload" href="https://g.oaes.cc/oae/nuxt/css/cfd9421.css" as="style"><link rel="preload" href="https://g.oaes.cc/oae/nuxt/3fa47a4.js" as="script"><link rel="preload" href="https://g.oaes.cc/oae/nuxt/css/686b6ba.css" as="style"><link rel="preload" href="https://g.oaes.cc/oae/nuxt/9d41c4b.js" as="script"><link rel="preload" href="https://g.oaes.cc/oae/nuxt/css/cab3d9c.css" as="style"><link rel="preload" href="https://g.oaes.cc/oae/nuxt/ae6e07b.js" as="script"><link rel="stylesheet" href="https://g.oaes.cc/oae/nuxt/css/8176b15.css"><link rel="stylesheet" href="https://g.oaes.cc/oae/nuxt/css/cfd9421.css"><link rel="stylesheet" href="https://g.oaes.cc/oae/nuxt/css/686b6ba.css"><link rel="stylesheet" href="https://g.oaes.cc/oae/nuxt/css/cab3d9c.css"> </head> <body > <div data-server-rendered="true" id="__nuxt"><div id="__layout"><div data-fetch-key="qklayoutc:0"><div><div class="PcComment" data-v-662e0091><div class="ipad_bg" style="display:none;" data-v-662e0091></div> <div class="head_top" data-v-662e0091><div class="wrapper head_box" data-v-662e0091><span class="qk_jx" data-v-662e0091><img src="https://i.oaes.cc/upload/journal_logo/ais.png" alt data-v-662e0091></span> <a href="/ais" aria-current="page" class="qk_a_name nuxt-link-exact-active nuxt-link-active" data-v-662e0091><span class="title font20" data-v-662e0091>Artificial Intelligence Surgery</span></a> <div class="top_img" data-v-662e0091><a href="https://www.scopus.com/sourceid/21101189039" target="_blank" data-v-662e0091><img src="https://i.oaes.cc/uploads/20240813/b7358d0632aa413fa84630ef0a2fb7a0.png" alt data-v-662e0091></a><a href="" target="_blank" data-v-662e0091><img src="https://i.oaes.cc/uploads/20240506/ea3d9071c35b4bf3982ffe25f1083620.png" alt data-v-662e0091></a></div> <div class="oae_menu_box" data-v-662e0091><a href="/alljournals" data-v-662e0091><span data-v-662e0091>All Journals</span></a></div> <span class="search" data-v-662e0091><i class="icon-search icon_right font24" data-v-662e0091></i> <span data-v-662e0091>Search</span></span> <span class="go_oae" data-v-662e0091><a href="https://oaemesas.com/login?JournalId=ais" target="_blank" data-v-662e0091><i class="icon-login-line icon_right font24" data-v-662e0091></i> <span data-v-662e0091>Log In</span></a></span></div></div> <div class="cg" style="height: 41px" data-v-662e0091></div>  <div class="head_text" style="border-bottom:3px solid rgb(3,0,114);" data-v-662e0091><div class="head_search wrapper" data-v-662e0091><div class="box_btn" data-v-662e0091><div class="qk_miss" data-v-662e0091><img src="https://i.oaes.cc/uploads/20231110/14bc775310574f91b457ff09d6c6d950.jpg" alt class="qk_fm" data-v-662e0091> <div class="miss_right" data-v-662e0091><div class="miss_btn" data-v-662e0091><span data-v-662e0091><span class="font_b" data-v-662e0091>Editor-in-Chief:</span> Andrew A. Gumbs</span></div> <div class="miss_btn" data-v-662e0091><div class="text_index" data-v-662e0091><span class="font_b" data-v-662e0091>Indexing: </span> <span data-v-662e0091><a href="https://www.oaepublish.com/news/ais.847" target="_blank" data-v-662e0091>ESCI</a><span class="xing_d" data-v-662e0091>, </span></span><span data-v-662e0091><a href="https://www.scopus.com/sourceid/21101189039" target="_blank" data-v-662e0091>Scopus</a><span class="xing_d" data-v-662e0091>, </span></span><span data-v-662e0091><a href="https://app.dimensions.ai/discover/publication?and_facet_source_title=jour.1410374" target="_blank" data-v-662e0091>Dimensions</a><span class="xing_d" data-v-662e0091>, </span></span><span data-v-662e0091><a 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Submit your work this December and enjoy the benefits of our Christmas Special!<br>🎅 Happy Holidays and happy publishing with <i>AIS</i>🎅</span></div></div> <img src="https://i.oaes.cc/uploads/20241120/479e066a5dff491989fa162b992b4ccd.jpg" alt data-v-5c8e3c6d></a></div><div class="swiper-slide" data-v-5c8e3c6d><a href="https://www.oaepublish.com/collections/ais.13" data-v-5c8e3c6d><div class="tit" data-v-5c8e3c6d><div class="title" data-v-5c8e3c6d><a href="https://www.oaepublish.com/collections/ais.13" data-v-5c8e3c6d><span data-v-5c8e3c6d><i>Artificial Intelligence Surgery</i> Launches The First Women Special Collection </span></a></div> <div class="title_sm" data-v-5c8e3c6d><span data-v-5c8e3c6d><i>AIS</i> is proud to announce our first Special Collection chaired by Prof. Gaya Spolverato and Prof. Sharona B Ross, dedicated to the power and achievements of women surgeons in the dynamic field of AI-driven surgery.</span></div></div> <img src="https://i.oaes.cc/uploads/20241111/e4ac21d4892649e0bb926cd7af392b19.jpg" alt data-v-5c8e3c6d></a></div><div class="swiper-slide" data-v-5c8e3c6d><a href="https://www.oaepublish.com/news/ais.847" data-v-5c8e3c6d><div class="tit" data-v-5c8e3c6d><div class="title" data-v-5c8e3c6d><a href="https://www.oaepublish.com/news/ais.847" data-v-5c8e3c6d><span data-v-5c8e3c6d><i>Artificial Intelligence Surgery</i> Accepted for Inclusion in the Emerging Sources Citation Index (ESCI) in August 2024 </span></a></div> <div class="title_sm" data-v-5c8e3c6d><span data-v-5c8e3c6d>AIS has been officially indexed by Emerging Sources Citation Index (ESCI) on August 29th, 2024. </span></div></div> <img src="https://i.oaes.cc/uploads/20240830/ff9a5000b14440e4883977af084092a3.jpg" alt data-v-5c8e3c6d></a></div><div class="swiper-slide" data-v-5c8e3c6d><a href="https://www.oaepublish.com/specials/ais.1105" data-v-5c8e3c6d><div class="tit" data-v-5c8e3c6d><div class="title" data-v-5c8e3c6d><a href="https://www.oaepublish.com/specials/ais.1105" data-v-5c8e3c6d><span data-v-5c8e3c6d>Congratulations! 14 articles have been published in this special issue! </span></a></div> <div class="title_sm" data-v-5c8e3c6d><span data-v-5c8e3c6d>The Special Issue regarding AI in HPB surgery has been completed successfully with 14 articles. Sincere gratitude to our guest editors Prof. Henry A. Pitt and Prof. Derek A. O'Reilly. Welcome to read the E-book. </span></div></div> <img src="https://i.oaes.cc/uploads/20240802/d91e7388c5c74a749b93a8acd2dc7007.jpg" alt data-v-5c8e3c6d></a></div><div class="swiper-slide" data-v-5c8e3c6d><a href="https://www.oaepublish.com/specials/ais.2043" data-v-5c8e3c6d><div class="tit" data-v-5c8e3c6d><div class="title" data-v-5c8e3c6d><a href="https://www.oaepublish.com/specials/ais.2043" data-v-5c8e3c6d><span data-v-5c8e3c6d>Call for Paper</span></a></div> <div class="title_sm" data-v-5c8e3c6d><span data-v-5c8e3c6d>Prof. Michel Gagner’s special issue is calling for papers regarding AI in Bariatric Surgery. Welcome ro submit your articles!</span></div></div> <img src="https://i.oaes.cc/uploads/20240523/18860742b6db404c8240277f2a8bb60d.jpg" alt data-v-5c8e3c6d></a></div></div> <div class="swiper-pagination" style="display:;" data-v-5c8e3c6d></div> <div class="swiper-button-prev" style="display:;" data-v-5c8e3c6d><img src="https://g.oaes.cc/oae/nuxt/img/slide-left30x40_@3x.5042b29.png" alt class="btn_swiper" data-v-5c8e3c6d></div> <div class="swiper-button-next" style="display:;" data-v-5c8e3c6d><img src="https://g.oaes.cc/oae/nuxt/img/slide-right30x40_@3x.21cefa8.png" alt class="btn_swiper" data-v-5c8e3c6d></div></div></div></div></div></div> <div class="grid-content index_left pad_r_10" data-v-2c8370e1> <div class="hot_art" data-v-2c8370e1><div data-v-ab8748fc data-v-2c8370e1><div class="PcTitle" data-v-ab8748fc><div class="top_line" data-v-ab8748fc></div> <div class="tit_box" data-v-ab8748fc><a href="/ais/featured" class="title_h" data-v-ab8748fc>Featured Articles<i class="el-icon-arrow-right" data-v-ab8748fc></i></a></div> <div class="line_btn" style="margin-top: 10px;" data-v-ab8748fc></div></div></div> <div class="art_item" data-v-2c8370e1><a href="/articles/ais.2022.11" data-v-2c8370e1><h4 class="article-header bor_btn" data-v-2c8370e1>The challenges of deep learning in artificial intelligence and autonomous actions in surgery: a literature review</h4></a></div><div class="art_item" data-v-2c8370e1><a href="/articles/ais.2021.15" data-v-2c8370e1><h4 class="article-header bor_btn" data-v-2c8370e1>Computer vision and machine learning for medical image analysis: recent advances, challenges, and way forward</h4></a></div><div class="art_item" data-v-2c8370e1><a href="/articles/ais.2022.10" data-v-2c8370e1><h4 class="article-header bor_btn" data-v-2c8370e1>White paper: definitions of artificial intelligence and autonomous actions in clinical surgery</h4></a></div></div> <div data-v-0dd4c6f5 data-v-2c8370e1><div class="New_box" data-v-0dd4c6f5><div data-v-ab8748fc data-v-0dd4c6f5><div class="PcTitle" data-v-ab8748fc><div class="top_line" data-v-ab8748fc></div> <div class="tit_box" data-v-ab8748fc><a href="/ais/ai_podcast" class="title_h" data-v-ab8748fc>Academic Talks<i class="el-icon-arrow-right" data-v-ab8748fc></i></a></div> <div class="line_btn" style="margin-top: 10px;" data-v-ab8748fc></div></div></div> <div class="New_item" data-v-0dd4c6f5><div class="img" data-v-0dd4c6f5><img src="https://i.oaes.cc/uploads/20241105/930acccbc6df4053ae45dfeef09315c7.png" alt data-itemid="459" data-itemhref="https://v.oaes.cc/uploads/20241105/049625faa328464a8b1fbbc2eb24f3c4.mp4" data-itemimg="https://i.oaes.cc/uploads/20241105/930acccbc6df4053ae45dfeef09315c7.png" data-v-0dd4c6f5> <i data-itemid="459" data-itemhref="https://v.oaes.cc/uploads/20241105/049625faa328464a8b1fbbc2eb24f3c4.mp4" data-itemimg="https://i.oaes.cc/uploads/20241105/930acccbc6df4053ae45dfeef09315c7.png" class="bo_icon" data-v-0dd4c6f5></i></div> <div class="cont" data-v-0dd4c6f5><h4 class="New_header ellip5" data-v-0dd4c6f5>Episode 57: Interview of Prof. Iyer Shridhar Ganpathi</h4> <div class="video_num" data-v-0dd4c6f5><span class="em-margin-right" data-v-0dd4c6f5><i class="icon-play-line icon_right4" data-v-0dd4c6f5></i> </span> <span class="em-margin-right com_is_zan" data-v-0dd4c6f5><i class="icon-like-line zankong icon_right4" data-v-0dd4c6f5></i> <i class="icon-like-flat zanfill icon_right4" data-v-0dd4c6f5></i> <i class="ZanNum" data-v-0dd4c6f5></i> <i class="ZanNumj" data-v-0dd4c6f5>NaN</i></span></div></div></div></div></div>  <div data-v-035d42c0 data-v-2c8370e1><div class="article_box" data-v-035d42c0><div class="top_line" data-v-035d42c0></div> <div class="tit_box" data-v-035d42c0><h2 class="title_h" data-v-035d42c0><a href="/ais/articles" class="title_h" data-v-035d42c0>Articles</a></h2> <div class="art_tab" data-v-035d42c0><span class="btn_lin" data-v-035d42c0>Most Recent</span> <span class="line" data-v-035d42c0>|</span> <span data-v-035d42c0>Most Viewed</span> <span class="line" data-v-035d42c0>|</span> <span data-v-035d42c0>Most Downloaded</span></div> <a href="/ais/articles?sort=lasted" class="title_h" data-v-035d42c0><i class="el-icon-arrow-right" data-v-035d42c0></i></a>  </div> <div class="line_btn" style="margin-top: 10px;" data-v-035d42c0></div> <div class="article_list" data-v-035d42c0><div class="article_item" data-v-9152e652 data-v-035d42c0><div class="article_left all_width" data-v-9152e652><div class="article_header" data-v-9152e652><a href="/articles/ais.2024.40" data-v-9152e652><h4 class="art_head" data-v-9152e652>Pseudarthrosis following adult spinal deformity surgery may be predicted with preoperative MRI adipose tissue features: an artificial intelligence study on raw 3D imaging</h4></a></div>  <div class="text_cont" data-v-9152e652><div class="article_author font-999" data-v-9152e652>Graham W. 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Submit your work this December and enjoy the benefits of our Christmas Special!<br>🎅 Happy Holidays and happy publishing with <i>AIS</i>🎅</span></div></div> <img src="https://i.oaes.cc/uploads/20241120/479e066a5dff491989fa162b992b4ccd.jpg" alt data-v-5c8e3c6d></a></div><div class="swiper-slide" data-v-5c8e3c6d><a href="https://www.oaepublish.com/collections/ais.13" data-v-5c8e3c6d><div class="tit" data-v-5c8e3c6d><div class="title" data-v-5c8e3c6d><a href="https://www.oaepublish.com/collections/ais.13" data-v-5c8e3c6d><span data-v-5c8e3c6d><i>Artificial Intelligence Surgery</i> Launches The First Women Special Collection </span></a></div> <div class="title_sm" data-v-5c8e3c6d><span data-v-5c8e3c6d><i>AIS</i> is proud to announce our first Special Collection chaired by Prof. Gaya Spolverato and Prof. Sharona B Ross, dedicated to the power and achievements of women surgeons in the dynamic field of AI-driven surgery.</span></div></div> <img src="https://i.oaes.cc/uploads/20241111/e4ac21d4892649e0bb926cd7af392b19.jpg" alt data-v-5c8e3c6d></a></div><div class="swiper-slide" data-v-5c8e3c6d><a href="https://www.oaepublish.com/news/ais.847" data-v-5c8e3c6d><div class="tit" data-v-5c8e3c6d><div class="title" data-v-5c8e3c6d><a href="https://www.oaepublish.com/news/ais.847" data-v-5c8e3c6d><span data-v-5c8e3c6d><i>Artificial Intelligence Surgery</i> Accepted for Inclusion in the Emerging Sources Citation Index (ESCI) in August 2024 </span></a></div> <div class="title_sm" data-v-5c8e3c6d><span data-v-5c8e3c6d>AIS has been officially indexed by Emerging Sources Citation Index (ESCI) on August 29th, 2024. </span></div></div> <img src="https://i.oaes.cc/uploads/20240830/ff9a5000b14440e4883977af084092a3.jpg" alt data-v-5c8e3c6d></a></div><div class="swiper-slide" data-v-5c8e3c6d><a href="https://www.oaepublish.com/specials/ais.1105" data-v-5c8e3c6d><div class="tit" data-v-5c8e3c6d><div class="title" data-v-5c8e3c6d><a href="https://www.oaepublish.com/specials/ais.1105" data-v-5c8e3c6d><span data-v-5c8e3c6d>Congratulations! 14 articles have been published in this special issue! </span></a></div> <div class="title_sm" data-v-5c8e3c6d><span data-v-5c8e3c6d>The Special Issue regarding AI in HPB surgery has been completed successfully with 14 articles. Sincere gratitude to our guest editors Prof. Henry A. Pitt and Prof. Derek A. O'Reilly. Welcome to read the E-book. </span></div></div> <img src="https://i.oaes.cc/uploads/20240802/d91e7388c5c74a749b93a8acd2dc7007.jpg" alt data-v-5c8e3c6d></a></div><div class="swiper-slide" data-v-5c8e3c6d><a href="https://www.oaepublish.com/specials/ais.2043" data-v-5c8e3c6d><div class="tit" data-v-5c8e3c6d><div class="title" data-v-5c8e3c6d><a href="https://www.oaepublish.com/specials/ais.2043" data-v-5c8e3c6d><span data-v-5c8e3c6d>Call for Paper</span></a></div> <div class="title_sm" data-v-5c8e3c6d><span data-v-5c8e3c6d>Prof. Michel Gagner’s special issue is calling for papers regarding AI in Bariatric Surgery. 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{layout:"qklayouti",data:[{indexTop:{banner:[{id:1072,type:R,title:"🎄Christmas Special🎄",sub_title:"This “Christmas Special” is our way of saying thank you to the academic community for your invaluable contributions. Submit your work this December and enjoy the benefits of our Christmas Special!\u003Cbr\u003E🎅 Happy Holidays and happy publishing with \u003Ci\u003EAIS\u003C\u002Fi\u003E🎅",href:b_,target:g,img:"https:\u002F\u002Fi.oaes.cc\u002Fuploads\u002F20241120\u002F479e066a5dff491989fa162b992b4ccd.jpg",mobile_img:a},{id:b$,type:R,title:"\u003Ci\u003EArtificial Intelligence Surgery\u003C\u002Fi\u003E Launches The First Women Special Collection\r\n",sub_title:"\u003Ci\u003EAIS\u003C\u002Fi\u003E is proud to announce our first Special Collection chaired by Prof. Gaya Spolverato and Prof. Sharona B Ross, dedicated to the power and achievements of women surgeons in the dynamic field of AI-driven surgery.",href:"https:\u002F\u002Fwww.oaepublish.com\u002Fcollections\u002Fais.13",target:g,img:"https:\u002F\u002Fi.oaes.cc\u002Fuploads\u002F20241111\u002Fe4ac21d4892649e0bb926cd7af392b19.jpg",mobile_img:a},{id:995,type:R,title:"\u003Ci\u003EArtificial Intelligence Surgery\u003C\u002Fi\u003E Accepted for Inclusion in the Emerging Sources Citation Index (ESCI) in August 2024\r\n",sub_title:"AIS has been officially indexed by Emerging Sources Citation Index (ESCI) on August 29th, 2024.\r\n",href:ca,target:g,img:"https:\u002F\u002Fi.oaes.cc\u002Fuploads\u002F20240830\u002Fff9a5000b14440e4883977af084092a3.jpg",mobile_img:a},{id:974,type:R,title:"Congratulations! 14 articles have been published in this special issue!\r\n",sub_title:"The Special Issue regarding AI in HPB surgery has been completed successfully with 14 articles. Sincere gratitude to our guest editors Prof. Henry A. Pitt and Prof. Derek A. O'Reilly. Welcome to read the E-book.\r\n",href:"https:\u002F\u002Fwww.oaepublish.com\u002Fspecials\u002Fais.1105",target:g,img:"https:\u002F\u002Fi.oaes.cc\u002Fuploads\u002F20240802\u002Fd91e7388c5c74a749b93a8acd2dc7007.jpg",mobile_img:a},{id:875,type:R,title:"Call for Paper",sub_title:"Prof. Michel Gagner’s special issue is calling for papers regarding AI in Bariatric Surgery. Welcome ro submit your articles!",href:"https:\u002F\u002Fwww.oaepublish.com\u002Fspecials\u002Fais.2043",target:g,img:"https:\u002F\u002Fi.oaes.cc\u002Fuploads\u002F20240523\u002F18860742b6db404c8240277f2a8bb60d.jpg",mobile_img:a}],articles:[{url_doi:bm,title:bn,id:312},{url_doi:aB,title:aC,id:311},{url_doi:aD,title:aE,id:310}],video:{id:459,title:"Episode 57: Interview of Prof. Iyer Shridhar Ganpathi",video_url:cb,img_url:"https:\u002F\u002Fi.oaes.cc\u002Fuploads\u002F20241105\u002F930acccbc6df4053ae45dfeef09315c7.png",link:cb,journal_id:t,type:"academic",videos_home_url:"\u002Fai_podcast"}},indexMid:{articles:{recent:[{article_id:"7418",title:"Pseudarthrosis following adult spinal deformity surgery may be predicted with preoperative MRI adipose tissue features: an artificial intelligence study on raw 3D imaging",image:e,tag:"401-10",doi:"10.20517\u002Fais.2024.40",date_published:"1732982400",section:"Original Article",authors:"Graham W. Johnson\u003Ca href='https:\u002F\u002Forcid.org\u002F0000-0002-9154-4315' target='_blank'\u003E\u003Cimg src='https:\u002F\u002Fi.oaes.cc\u002Fimages\u002Forcid.png' class='author_id' alt='Graham W. Johnson'\u003E\u003C\u002Fa\u003E, ... Scott L. Zuckerman",journal_id:o,volume:p,year:S,section_id:cc,special_name:cd,url_doi:"ais.2024.40",pdf:"https:\u002F\u002Ff.oaes.cc\u002Fxmlpdf\u002F1f4afb7d-527a-4196-9a31-4b4a2cfce45f\u002Fais4040.pdf",video_url:a,allauthors:"\u003Cimg src='https:\u002F\u002Fi.oaes.cc\u002Fimages\u002Fdefault_photo.png' class='author_photo' alt='Graham W. Johnson'\u003E Graham W. Johnson\u003Ca href='https:\u002F\u002Forcid.org\u002F0000-0002-9154-4315' target='_blank'\u003E\u003Cimg src='https:\u002F\u002Fi.oaes.cc\u002Fimages\u002Forcid.png' class='author_id' alt='Graham W. Johnson'\u003E\u003C\u002Fa\u003E, \u003Cimg src='https:\u002F\u002Fi.oaes.cc\u002Fimages\u002Fdefault_photo.png' class='author_photo' alt='Hani Chanbour'\u003E Hani Chanbour, \u003Cimg src='https:\u002F\u002Fi.oaes.cc\u002Fimages\u002Fdefault_photo.png' class='author_photo' alt='Derek J. Doss'\u003E Derek J. Doss, \u003Cimg src='https:\u002F\u002Fi.oaes.cc\u002Fimages\u002Fdefault_photo.png' class='author_photo' alt='Ghassan S. Makhoul'\u003E Ghassan S. Makhoul, \u003Cimg src='https:\u002F\u002Fi.oaes.cc\u002Fimages\u002Fdefault_photo.png' class='author_photo' alt='Amir M. Abtahi'\u003E Amir M. Abtahi, \u003Cimg src='https:\u002F\u002Fi.oaes.cc\u002Fimages\u002Fdefault_photo.png' class='author_photo' alt='Byron F. Stephens'\u003E Byron F. Stephens, \u003Cimg src='https:\u002F\u002Fi.oaes.cc\u002Fimages\u002Fdefault_photo.png' class='author_photo' alt='Scott L. Zuckerman'\u003E Scott L. Zuckerman",journal_path:k,video_img:a,image_list:e,abstract:"\u003Cp\u003E\u003Cb\u003EAim:\u003C\u002Fb\u003E The purpose of this study is to investigate the utility of incorporating magnetic resonance imaging (MRI) into an artificial intelligence (AI) model to preoperatively predict pseudarthrosis for patients undergoing adult spinal deformity (ASD) surgery.\u003C\u002Fp\u003E\u003Cp\u003E\u003Cb\u003EMethods:\u003C\u002Fb\u003E A retrospective cohort study was conducted on patients undergoing ASD surgery at Vanderbilt University Medical Center with at least 2 years of follow-up. We first collected demographic variables and measured traditional radiographic variables with Surgimap software. The primary outcome of interest was pseudarthrosis, defined as mechanical pain without evidence of bony union with or without a rod fracture. Next, cohort differences between patients diagnosed with and without pseudarthrosis were evaluated with \u003Ci\u003Et\u003C\u002Fi\u003E-tests for continuous variables and chi-squared tests for categorical variables using Bonferroni-Holm multiple comparison correction. Using a subpopulation of patients with preoperative thoracic MRI available, a three-dimensional convolutional neural network (3D-CNN) with five-fold nested cross-validation was developed to predict pseudarthrosis - accuracy was evaluated with the Youden index. Finally, class activation mapping (CAM) was conducted to visualize the MRI features utilized by the model for accurate classifications.\u003C\u002Fp\u003E\u003Cp\u003E\u003Cb\u003EResults:\u003C\u002Fb\u003E Of 191 patients undergoing ASD surgery, the demographic and traditional radiographic variables were collected, and only age was observed to be significantly different between the patients diagnosed with pseudarthrosis (69.9 ± 10.1 years old) and those without (60.9 ± 19.9), with a \u003Ci\u003Et\u003C\u002Fi\u003E-test \u003Ci\u003EP\u003C\u002Fi\u003E-value of 0.003. The 3D-CNN demonstrated an average Youden index of 0.49 ± 0.25 on the withheld data, with a \u003Ci\u003EP\u003C\u002Fi\u003E-value of 5.50e-3 compared to an equivocal null model. Finally, CAM consistently revealed posterior adipose tissue to be most important in preoperatively predicting pseudarthrosis.\u003C\u002Fp\u003E\u003Cp\u003E\u003Cb\u003EConclusion:\u003C\u002Fb\u003E Adipose tissue features in MRI, independent of body mass index (BMI), may be useful for preoperatively predicting pseudarthrosis. Overall, this work demonstrates the capabilities of raw imaging AI in spine surgery and can serve as the basis for a deeper biological inquiry into the pathogenesis of pseudarthrosis.\u003C\u002Fp\u003E"},{article_id:"7344",title:"Beyond AI and robotics: the dawn of surgical automation in spine surgery",image:e,tag:"387-400",doi:"10.20517\u002Fais.2024.34",date_published:"1731254400",section:u,authors:"Nishanth S. Sadagopan, ... Najib E. El Tecle\u003Ca href='https:\u002F\u002Forcid.org\u002F0000-0002-5242-1646' target='_blank'\u003E\u003Cimg src='https:\u002F\u002Fi.oaes.cc\u002Fimages\u002Forcid.png' class='author_id' alt='Najib E. El Tecle'\u003E\u003C\u002Fa\u003E",journal_id:o,volume:p,year:S,section_id:cc,special_name:cd,url_doi:"ais.2024.34",pdf:"https:\u002F\u002Ff.oaes.cc\u002Fxmlpdf\u002Ff07027a5-a42e-4cfe-8dd1-d587fd0a41f2\u002Fais4034.pdf",video_url:a,allauthors:"\u003Cimg src='https:\u002F\u002Fi.oaes.cc\u002Fimages\u002Fdefault_photo.png' class='author_photo' alt='Nishanth S. Sadagopan'\u003E Nishanth S. Sadagopan, \u003Cimg src='https:\u002F\u002Fi.oaes.cc\u002Fimages\u002Fdefault_photo.png' class='author_photo' alt='Dillan Prasad'\u003E Dillan Prasad, \u003Cimg src='https:\u002F\u002Fi.oaes.cc\u002Fimages\u002Fdefault_photo.png' class='author_photo' alt='Rishi Jain'\u003E Rishi Jain, \u003Cimg src='https:\u002F\u002Fi.oaes.cc\u002Fimages\u002Fdefault_photo.png' class='author_photo' alt='Christopher Ahuja'\u003E Christopher Ahuja, \u003Cimg src='https:\u002F\u002Fi.oaes.cc\u002Fimages\u002Fdefault_photo.png' class='author_photo' alt='Nader S. Dahdaleh'\u003E Nader S. Dahdaleh, \u003Cimg src='https:\u002F\u002Fi.oaes.cc\u002Fimages\u002Fdefault_photo.png' class='author_photo' alt='Najib E. El Tecle'\u003E Najib E. El Tecle\u003Ca href='https:\u002F\u002Forcid.org\u002F0000-0002-5242-1646' target='_blank'\u003E\u003Cimg src='https:\u002F\u002Fi.oaes.cc\u002Fimages\u002Forcid.png' class='author_id' alt='Najib E. El Tecle'\u003E\u003C\u002Fa\u003E",journal_path:k,video_img:a,image_list:e,abstract:"\u003Cp\u003EArtificial intelligence (AI), deep learning (DL), and machine learning (ML) algorithms are revolutionizing spine surgery. Soon, these technologies may allow the integration of automated devices into clinical practice. The roles of such devices are yet to be imagined and then developed, but one could assume that automated surgical devices can assist spine surgeons in a variety of ways, such as contextual guidance, precise screw placements, or intraoperative monitoring. In the not-too-distant future, such devices may be able to perform entire surgeries autonomously. Current literature suggests that advancements toward autonomous robotic surgery may improve surgical approaches and reduce negative clinical variation in spine surgery outcomes. This review aims to examine the current trends, practices, and advancements in surgical automation and provide an overview of the stages of automation of devices currently employed within spine surgery.\u003C\u002Fp\u003E"},{article_id:"7326",title:"Transformative role of artificial intelligence in plastic and reconstructive surgery: innovations, applications and future directions",image:e,tag:"376-86",doi:"10.20517\u002Fais.2024.52",date_published:"1730822400",section:u,authors:"Matthias Johannes Novotny\u003Ca href='https:\u002F\u002Forcid.org\u002F0009-0005-8214-7288' target='_blank'\u003E\u003Cimg src='https:\u002F\u002Fi.oaes.cc\u002Fimages\u002Forcid.png' class='author_id' alt='Matthias Johannes Novotny'\u003E\u003C\u002Fa\u003E, ... Christine Radtke\u003Ca href='https:\u002F\u002Forcid.org\u002F0000-0001-6877-5038' target='_blank'\u003E\u003Cimg src='https:\u002F\u002Fi.oaes.cc\u002Fimages\u002Forcid.png' class='author_id' alt='Christine Radtke'\u003E\u003C\u002Fa\u003E",journal_id:o,volume:p,year:S,section_id:ce,special_name:cf,url_doi:"ais.2024.52",pdf:"https:\u002F\u002Ff.oaes.cc\u002Fxmlpdf\u002F39f1b32e-e7b4-4a2b-9404-a55338b75d59\u002Fais4052.pdf",video_url:a,allauthors:"\u003Cimg src='https:\u002F\u002Fi.oaes.cc\u002Fimages\u002Fdefault_photo.png' class='author_photo' alt='Matthias Johannes Novotny'\u003E Matthias Johannes Novotny\u003Ca href='https:\u002F\u002Forcid.org\u002F0009-0005-8214-7288' target='_blank'\u003E\u003Cimg src='https:\u002F\u002Fi.oaes.cc\u002Fimages\u002Forcid.png' class='author_id' alt='Matthias Johannes Novotny'\u003E\u003C\u002Fa\u003E, \u003Cimg src='https:\u002F\u002Fi.oaes.cc\u002Fimages\u002Fdefault_photo.png' class='author_photo' alt='Anna Fast'\u003E Anna Fast\u003Ca href='https:\u002F\u002Forcid.org\u002F0009-0003-8038-6109' target='_blank'\u003E\u003Cimg src='https:\u002F\u002Fi.oaes.cc\u002Fimages\u002Forcid.png' class='author_id' alt='Anna Fast'\u003E\u003C\u002Fa\u003E, \u003Cimg src='https:\u002F\u002Fi.oaes.cc\u002Fimages\u002Fdefault_photo.png' class='author_photo' alt='Christine Radtke'\u003E Christine Radtke\u003Ca href='https:\u002F\u002Forcid.org\u002F0000-0001-6877-5038' target='_blank'\u003E\u003Cimg src='https:\u002F\u002Fi.oaes.cc\u002Fimages\u002Forcid.png' class='author_id' alt='Christine Radtke'\u003E\u003C\u002Fa\u003E",journal_path:k,video_img:a,image_list:e,abstract:"\u003Cp\u003EThis review explores the current applications, benefits, and challenges of artificial intelligence (AI) in plastic, reconstructive, and aesthetic surgery. In recent years, AI has found its way into everyday life, including the healthcare sector. To deepen the understanding of the use and handling of AI in plastic and reconstructive surgery, this review provides valuable insights into modern practices, illustrated with real examples and potential future applications. While the advantages of AI are obvious, the disadvantages cannot be ignored. This review aims to highlight possible risks, dangers, and sources of error inherent in AI itself and its applications. Therefore, this paper seeks to address possible concerns and questions about AI in plastic surgery while offering a realistically neutral insight. Additionally, fundamental ethical and legal principles will be discussed, as well as possible “rules of the game” for the application and integration of AI in surgery. Innovations in this field are often hailed as miracles, making it crucial to evaluate them critically and objectively. Although progress in AI cannot and should not be halted, it is important to strengthen the trained approach and always look at the whole picture.\u003C\u002Fp\u003E"},{article_id:"7320",title:"A review of artificial intelligence in wound care",image:e,tag:"364-75",doi:"10.20517\u002Fais.2024.68",date_published:"1730649600",section:u,authors:"Ovya Ganesan, ... Dennis Orgill",journal_id:o,volume:p,year:S,section_id:ce,special_name:cf,url_doi:"ais.2024.68",pdf:"https:\u002F\u002Ff.oaes.cc\u002Fxmlpdf\u002F81be2e36-b06d-4e30-baab-db45d92e5536\u002Fais4068.pdf",video_url:a,allauthors:"\u003Cimg src='https:\u002F\u002Fi.oaes.cc\u002Fimages\u002Fdefault_photo.png' class='author_photo' alt='Ovya Ganesan'\u003E Ovya Ganesan, \u003Cimg src='https:\u002F\u002Fi.oaes.cc\u002Fimages\u002Fdefault_photo.png' class='author_photo' alt='Miranda Xiao Morris'\u003E Miranda Xiao Morris, \u003Cimg src='https:\u002F\u002Fi.oaes.cc\u002Fimages\u002Fdefault_photo.png' class='author_photo' alt='Lifei Guo'\u003E Lifei Guo, \u003Cimg src='https:\u002F\u002Fi.oaes.cc\u002Fimages\u002Fdefault_photo.png' class='author_photo' alt='Dennis Orgill'\u003E Dennis Orgill",journal_path:k,video_img:a,image_list:e,abstract:"\u003Cp\u003EOur aging population, diabetes, and obesity have fueled the growth of chronic wounds seen throughout the world. Often, wounds are a marker of poor health that leads to increased mortality rates. However, the diagnosis and treatment of these wounds are challenging. Incorrectly differentiating between chronic wounds and other complex conditions can lead to adverse events. Artificial intelligence (AI) has been shown to offer some early benefits, and we hypothesized that it may enhance wound care but also carry some notable risks. We performed a detailed search using PubMed, Scopus, Cumulated Index in Nursing and Allied Health Literature, and Web of Science for AI applications in wound care. AI was found to be applied to wound diagnosis and characterization, wound monitoring for tissue change, daily therapy, and prevention and prognostics. AI made for more efficient and accurate wound assessments, less painful assessments of chronic wounds, more personalized treatment, and improved prognostic prediction capabilities. AI also allowed for more precise at-home observation and care, facilitating earlier wound treatment as needed. Challenges associated with AI included how to best allocate AI-assisted technologies equitably, how to safely maintain patient data, and how to diversify datasets for algorithm training. Because the algorithms are not transparent, validating findings may be challenging. AI presents a powerful tool in several aspects of advanced wound care and has the potential to improve diagnoses, accelerate healing, reduce pain, and improve the cost-effectiveness of wound care. More research needs to be done into how to best incorporate AI into daily clinical practice while keeping clinicians aware of the potential risks of using these evolving technologies.\u003C\u002Fp\u003E"},{article_id:"7310",title:"Application and use of artificial intelligence in colorectal cancer surgery: where are we?",image:e,tag:"348-63",doi:"10.20517\u002Fais.2024.26",date_published:"1730304000",section:u,authors:"Francesco Celotto\u003Ca href='https:\u002F\u002Forcid.org\u002F0000-0002-1881-0605' target='_blank'\u003E\u003Cimg src='https:\u002F\u002Fi.oaes.cc\u002Fimages\u002Forcid.png' class='author_id' alt='Francesco Celotto'\u003E\u003C\u002Fa\u003E, ... Gaya Spolverato\u003Ca href='https:\u002F\u002Forcid.org\u002F0000-0002-7275-2573' target='_blank'\u003E\u003Cimg src='https:\u002F\u002Fi.oaes.cc\u002Fimages\u002Forcid.png' class='author_id' alt='Gaya Spolverato'\u003E\u003C\u002Fa\u003E",journal_id:o,volume:p,year:S,section_id:e,special_name:a,url_doi:"ais.2024.26",pdf:"https:\u002F\u002Ff.oaes.cc\u002Fxmlpdf\u002Fb3010fe3-b72b-400f-8578-902238f1ed2e\u002Fais4026.pdf",video_url:a,allauthors:"\u003Cimg src='https:\u002F\u002Fi.oaes.cc\u002Fimages\u002Fdefault_photo.png' class='author_photo' alt='Francesco Celotto'\u003E Francesco Celotto\u003Ca href='https:\u002F\u002Forcid.org\u002F0000-0002-1881-0605' target='_blank'\u003E\u003Cimg src='https:\u002F\u002Fi.oaes.cc\u002Fimages\u002Forcid.png' class='author_id' alt='Francesco Celotto'\u003E\u003C\u002Fa\u003E, \u003Cimg src='https:\u002F\u002Fi.oaes.cc\u002Fimages\u002Fdefault_photo.png' class='author_photo' alt='Giulia Capelli'\u003E Giulia Capelli\u003Ca href='https:\u002F\u002Forcid.org\u002F0000-0001-6830-8958' target='_blank'\u003E\u003Cimg src='https:\u002F\u002Fi.oaes.cc\u002Fimages\u002Forcid.png' class='author_id' alt='Giulia Capelli'\u003E\u003C\u002Fa\u003E, \u003Cimg src='https:\u002F\u002Fi.oaes.cc\u002Fimages\u002Fdefault_photo.png' class='author_photo' alt='Stefania Ferrari'\u003E Stefania Ferrari\u003Ca href='https:\u002F\u002Forcid.org\u002F0000-0002-8908-0849' target='_blank'\u003E\u003Cimg src='https:\u002F\u002Fi.oaes.cc\u002Fimages\u002Forcid.png' class='author_id' alt='Stefania Ferrari'\u003E\u003C\u002Fa\u003E, \u003Cimg src='https:\u002F\u002Fi.oaes.cc\u002Fimages\u002Fdefault_photo.png' class='author_photo' alt='Marco Scarpa'\u003E Marco Scarpa, \u003Cimg src='https:\u002F\u002Fi.oaes.cc\u002Fimages\u002Fdefault_photo.png' class='author_photo' alt='Salvatore Pucciarelli'\u003E Salvatore Pucciarelli, \u003Cimg src='https:\u002F\u002Fi.oaes.cc\u002Fimages\u002Fdefault_photo.png' class='author_photo' alt='Gaya Spolverato'\u003E Gaya Spolverato\u003Ca href='https:\u002F\u002Forcid.org\u002F0000-0002-7275-2573' target='_blank'\u003E\u003Cimg src='https:\u002F\u002Fi.oaes.cc\u002Fimages\u002Forcid.png' class='author_id' alt='Gaya Spolverato'\u003E\u003C\u002Fa\u003E",journal_path:k,video_img:a,image_list:e,abstract:"\u003Cp\u003EAI is revolutionizing the landscape of colorectal cancer (CRC) surgery, permeating diverse facets ranging from intraoperative guidance to predictive modeling of postoperative outcomes. This scoping review aims to comprehensively delineate the breadth of artificial intelligence (AI) applications in CRC surgery. A search of PubMed, Embase, and Ebsco databases up to December 2023 was conducted, with registration in the international prospective register of systematic reviews (PROSPERO) (CRD42024502107). Sixty-two studies meeting stringent inclusion criteria were scrutinized, encompassing AI utilization in CRC surgery or the development of AI-driven tools for colorectal surgical practice. Five principal domains of AI application emerged: (i) Intraoperative guidance, leveraging real-time navigation, indocyanine green (ICG) angiography, and hyperspectral imaging (HSI) to enhance surgical precision; (ii) Image segmentation, facilitating phase recognition, tools recognition, and anatomical identification to optimize surgical visualization; (iii) Training and performance assessment, enabling objective evaluation and enhancement of surgical skills through AI-driven simulations and feedback mechanisms; (iv) Prediction of surgical complications, encompassing prognostication of anastomotic leakage (AL) or stricture, stoma requirements, and prediction of low anterior resection syndrome (LARS) and short-term postoperative complications; (v) Utilization of electronic health records (EHRs), harnessing AI algorithms to streamline data analysis and inform decision-making processes. This review underscores the paradigm-shifting impact of AI in CRC surgery, transcending conventional boundaries and catalyzing advancements across diverse surgical domains. Although many applications are still experimental, as AI continues to evolve, it promises to transform surgical practice, optimize outcomes, and revolutionize patient care. Embracing AI technologies is imperative for colorectal surgeons to remain at the vanguard of surgical innovation and deliver superior outcomes for CRC patients.\u003C\u002Fp\u003E"}],recent_ids:"7418,7344,7326,7320,7310",view:[{article_id:cg,title:ch,image:e,tag:ci,doi:cj,date_published:ck,section:cl,authors:cm,journal_id:o,volume:g,year:d,section_id:e,special_name:a,url_doi:cn,pdf:co,video_url:a,allauthors:"Andrew A. Gumbs, Silvana Perretta, Bernard d’Allemagne, Elie Chouillard",journal_path:k,video_img:a,image_list:e,abstract:a},{article_id:bo,title:aC,image:D,tag:bp,doi:bq,date_published:br,section:u,authors:bs,journal_id:o,volume:h,year:q,section_id:e,special_name:a,url_doi:aB,pdf:bt,video_url:a,allauthors:"Eyad Elyan, Pattaramon Vuttipittayamongkol, Pamela Johnston, Kyle Martin, Kyle McPherson, Carlos Francisco Moreno-García, Chrisina Jayne, Md. Mostafa Kamal Sarker",journal_path:k,video_img:a,image_list:D,abstract:bu},{article_id:bv,title:aE,image:E,tag:bw,doi:bx,date_published:by,section:bz,authors:bA,journal_id:o,volume:h,year:q,section_id:e,special_name:a,url_doi:aD,pdf:bB,video_url:a,allauthors:"Andrew A. Gumbs\u003Ca href='https:\u002F\u002Forcid.org\u002F0000-0002-7044-5318' target='_blank'\u003E\u003Cimg src='https:\u002F\u002Fi.oaes.cc\u002Fimages\u002Forcid.png' class='author_id' alt='Andrew A. Gumbs'\u003E\u003C\u002Fa\u003E, Frank Alexander, Konrad Karcz\u003Ca href='https:\u002F\u002Forcid.org\u002F0000-0002-4711-3630' target='_blank'\u003E\u003Cimg src='https:\u002F\u002Fi.oaes.cc\u002Fimages\u002Forcid.png' class='author_id' alt='Konrad Karcz'\u003E\u003C\u002Fa\u003E, Elie Chouillard\u003Ca href='https:\u002F\u002Forcid.org\u002F0000-0003-4100-7412' target='_blank'\u003E\u003Cimg src='https:\u002F\u002Fi.oaes.cc\u002Fimages\u002Forcid.png' class='author_id' alt='Elie Chouillard'\u003E\u003C\u002Fa\u003E, Roland Croner\u003Ca href='https:\u002F\u002Forcid.org\u002F0000-0001-6248-7086' target='_blank'\u003E\u003Cimg src='https:\u002F\u002Fi.oaes.cc\u002Fimages\u002Forcid.png' class='author_id' alt='Roland Croner'\u003E\u003C\u002Fa\u003E, Jasamine Coles-Black, Belinda de Simone\u003Ca href='https:\u002F\u002Forcid.org\u002F0000-0002-7956-3097' target='_blank'\u003E\u003Cimg src='https:\u002F\u002Fi.oaes.cc\u002Fimages\u002Forcid.png' class='author_id' alt='Belinda de Simone'\u003E\u003C\u002Fa\u003E, Michel Gagner\u003Ca href='https:\u002F\u002Forcid.org\u002F0000-0001-6068-0333' target='_blank'\u003E\u003Cimg src='https:\u002F\u002Fi.oaes.cc\u002Fimages\u002Forcid.png' class='author_id' alt='Michel Gagner'\u003E\u003C\u002Fa\u003E, Brice Gayet, Vincent Grasso, Alfredo Illanes, Takeaki Ishizawa\u003Ca href='https:\u002F\u002Forcid.org\u002F0000-0002-9534-6973' target='_blank'\u003E\u003Cimg src='https:\u002F\u002Fi.oaes.cc\u002Fimages\u002Forcid.png' class='author_id' alt='Takeaki Ishizawa'\u003E\u003C\u002Fa\u003E, Luca Milone\u003Ca href='https:\u002F\u002Forcid.org\u002F0000-0002-3603-7927' target='_blank'\u003E\u003Cimg src='https:\u002F\u002Fi.oaes.cc\u002Fimages\u002Forcid.png' class='author_id' alt='Luca Milone'\u003E\u003C\u002Fa\u003E, Mehmet Mahir Özmen\u003Ca href='https:\u002F\u002Forcid.org\u002F0000-0003-0649-0111' target='_blank'\u003E\u003Cimg src='https:\u002F\u002Fi.oaes.cc\u002Fimages\u002Forcid.png' class='author_id' alt='Mehmet Mahir Özmen'\u003E\u003C\u002Fa\u003E, Micaela Piccoli\u003Ca href='https:\u002F\u002Forcid.org\u002F0000-0003-0930-6770' target='_blank'\u003E\u003Cimg src='https:\u002F\u002Fi.oaes.cc\u002Fimages\u002Forcid.png' class='author_id' alt='Micaela Piccoli'\u003E\u003C\u002Fa\u003E, Stefanie Spiedel\u003Ca href='https:\u002F\u002Forcid.org\u002F0000-0002-4590-1908' target='_blank'\u003E\u003Cimg src='https:\u002F\u002Fi.oaes.cc\u002Fimages\u002Forcid.png' class='author_id' alt='Stefanie Spiedel'\u003E\u003C\u002Fa\u003E, Gaya Spolverato\u003Ca href='https:\u002F\u002Forcid.org\u002F0000-0002-7275-2573' target='_blank'\u003E\u003Cimg src='https:\u002F\u002Fi.oaes.cc\u002Fimages\u002Forcid.png' class='author_id' alt='Gaya Spolverato'\u003E\u003C\u002Fa\u003E, Patricia Sylla, Jaime Vilaça\u003Ca href='https:\u002F\u002Forcid.org\u002F0000-0001-8207-8124' target='_blank'\u003E\u003Cimg src='https:\u002F\u002Fi.oaes.cc\u002Fimages\u002Forcid.png' class='author_id' alt='Jaime Vilaça'\u003E\u003C\u002Fa\u003E, Mohammad Abu Hilal, Lee L. Swanström",journal_path:k,video_img:a,image_list:E,abstract:bC},{article_id:cp,title:bn,image:e,tag:cq,doi:cr,date_published:cs,section:ct,authors:cu,journal_id:o,volume:h,year:q,section_id:e,special_name:a,url_doi:bm,pdf:cv,video_url:a,allauthors:"Heba Taher, Vincent Grasso, Sherifa Tawfik, Andrew Gumbs",journal_path:k,video_img:a,image_list:e,abstract:cw},{article_id:cx,title:cy,image:aF,tag:cz,doi:cA,date_published:cB,section:u,authors:cC,journal_id:o,volume:h,year:q,section_id:e,special_name:a,url_doi:cD,pdf:cE,video_url:a,allauthors:"Martin Wagner\u003Ca href='https:\u002F\u002Forcid.org\u002F0000-0002-9831-9110' target='_blank'\u003E\u003Cimg src='https:\u002F\u002Fi.oaes.cc\u002Fimages\u002Forcid.png' class='author_id' alt='Martin Wagner'\u003E\u003C\u002Fa\u003E, Sebastian Bodenstedt, Marie Daum, Andre Schulze, Rayan Younis, Johanna Brandenburg, Fiona R. Kolbinger, Marius Distler, Lena Maier-Hein, Jürgen Weitz, Beat-Peter Müller-Stich, Stefanie Speidel\u003Ca href='https:\u002F\u002Forcid.org\u002F0000-0002-4590-1908' target='_blank'\u003E\u003Cimg src='https:\u002F\u002Fi.oaes.cc\u002Fimages\u002Forcid.png' class='author_id' alt='Stefanie Speidel'\u003E\u003C\u002Fa\u003E",journal_path:k,video_img:a,image_list:aF,abstract:cF}],view_ids:"3890,4684,4913,5162,4755",download:[{article_id:cg,title:ch,image:e,tag:ci,doi:cj,date_published:ck,section:cl,authors:cm,journal_id:o,volume:g,year:d,section_id:e,special_name:a,url_doi:cn,pdf:co,video_url:a,allauthors:"\u003Cimg src='https:\u002F\u002Fi.oaes.cc\u002Fimages\u002Fdefault_photo.png' class='author_photo' alt='Andrew A. Gumbs'\u003E Andrew A. Gumbs, \u003Cimg src='https:\u002F\u002Fi.oaes.cc\u002Fimages\u002Fdefault_photo.png' class='author_photo' alt='Silvana Perretta'\u003E Silvana Perretta, \u003Cimg src='https:\u002F\u002Fi.oaes.cc\u002Fimages\u002Fdefault_photo.png' class='author_photo' alt='Bernard d’Allemagne'\u003E Bernard d’Allemagne, \u003Cimg src='https:\u002F\u002Fi.oaes.cc\u002Fimages\u002Fdefault_photo.png' class='author_photo' alt='Elie Chouillard'\u003E Elie Chouillard",journal_path:k,video_img:a,image_list:e,abstract:a},{article_id:bo,title:aC,image:D,tag:bp,doi:bq,date_published:br,section:u,authors:bs,journal_id:o,volume:h,year:q,section_id:e,special_name:a,url_doi:aB,pdf:bt,video_url:a,allauthors:cG,journal_path:k,video_img:a,image_list:D,abstract:bu},{article_id:cx,title:cy,image:aF,tag:cz,doi:cA,date_published:cB,section:u,authors:cC,journal_id:o,volume:h,year:q,section_id:e,special_name:a,url_doi:cD,pdf:cE,video_url:a,allauthors:"\u003Cimg src='https:\u002F\u002Fi.oaes.cc\u002Fimages\u002Fdefault_photo.png' class='author_photo' alt='Martin Wagner'\u003E Martin Wagner\u003Ca href='https:\u002F\u002Forcid.org\u002F0000-0002-9831-9110' target='_blank'\u003E\u003Cimg src='https:\u002F\u002Fi.oaes.cc\u002Fimages\u002Forcid.png' class='author_id' alt='Martin Wagner'\u003E\u003C\u002Fa\u003E, \u003Cimg src='https:\u002F\u002Fi.oaes.cc\u002Fimages\u002Fdefault_photo.png' class='author_photo' alt='Sebastian Bodenstedt'\u003E Sebastian Bodenstedt, \u003Cimg src='https:\u002F\u002Fi.oaes.cc\u002Fimages\u002Fdefault_photo.png' class='author_photo' alt='Marie Daum'\u003E Marie Daum, \u003Cimg src='https:\u002F\u002Fi.oaes.cc\u002Fimages\u002Fdefault_photo.png' class='author_photo' alt='Andre Schulze'\u003E Andre Schulze, \u003Cimg src='https:\u002F\u002Fi.oaes.cc\u002Fimages\u002Fdefault_photo.png' class='author_photo' alt='Rayan Younis'\u003E Rayan Younis, \u003Cimg src='https:\u002F\u002Fi.oaes.cc\u002Fimages\u002Fdefault_photo.png' class='author_photo' alt='Johanna Brandenburg'\u003E Johanna Brandenburg, \u003Cimg src='https:\u002F\u002Fi.oaes.cc\u002Fimages\u002Fdefault_photo.png' class='author_photo' alt='Fiona R. Kolbinger'\u003E Fiona R. Kolbinger, \u003Cimg src='https:\u002F\u002Fi.oaes.cc\u002Fimages\u002Fdefault_photo.png' class='author_photo' alt='Marius Distler'\u003E Marius Distler, ... \u003Cimg src='https:\u002F\u002Fi.oaes.cc\u002Fimages\u002Fdefault_photo.png' class='author_photo' alt='Stefanie Speidel'\u003E Stefanie Speidel\u003Ca href='https:\u002F\u002Forcid.org\u002F0000-0002-4590-1908' target='_blank'\u003E\u003Cimg src='https:\u002F\u002Fi.oaes.cc\u002Fimages\u002Forcid.png' class='author_id' alt='Stefanie Speidel'\u003E\u003C\u002Fa\u003E",journal_path:k,video_img:a,image_list:aF,abstract:cF},{article_id:"5408",title:"Machine learning for prediction of postoperative complications after hepato-biliary and pancreatic surgery",image:e,tag:"1-13",doi:"10.20517\u002Fais.2022.31",date_published:"1675094400",section:u,authors:"Iestyn M. Shapey, Mustafa Sultan",journal_id:o,volume:m,year:"2023",section_id:"1105",special_name:bD,url_doi:"ais.2022.31",pdf:"https:\u002F\u002Ff.oaes.cc\u002Fxmlpdf\u002F1daac767-719f-483a-a489-9a096324605f\u002F5408.pdf",video_url:a,allauthors:"\u003Cimg src='https:\u002F\u002Fi.oaes.cc\u002Fimages\u002Fdefault_photo.png' class='author_photo' alt='Iestyn M. Shapey'\u003E Iestyn M. Shapey, \u003Cimg src='https:\u002F\u002Fi.oaes.cc\u002Fimages\u002Fdefault_photo.png' class='author_photo' alt='Mustafa Sultan'\u003E Mustafa Sultan",journal_path:k,video_img:a,image_list:e,abstract:"\u003Cp\u003EDecision making in Hepatobiliary and Pancreatic Surgery is challenging, not least because of the significant complications that may occur following surgery and the complexity of interventions to treat them. Machine Learning (ML) relates to the use of computer derived algorithms and systems to enhance knowledge in order to facilitate decision making and could be of great benefit to surgical patients. ML could be employed pre- or peri-operatively to shape treatment choices prospectively, or could be utilised in the post-hoc analysis of complications in order to inform future practice. ML could reduce errors by drawing attention to known risks of complications through supervised learning, and gain greater insights by identifying previously under-appreciated aspects of care through unsupervised learning. Accuracy, validity and integrity of data are of fundamental importance if predictive models generated by ML are to be successfully integrated into surgical practice. The choice of appropriate ML models and the interface between ML, traditional statistical methodologies and human expertise will also impact the potential to incorporate data science techniques into daily clinical practice.\u003C\u002Fp\u003E"},{article_id:bv,title:aE,image:E,tag:bw,doi:bx,date_published:by,section:bz,authors:bA,journal_id:o,volume:h,year:q,section_id:e,special_name:a,url_doi:aD,pdf:bB,video_url:a,allauthors:cH,journal_path:k,video_img:a,image_list:E,abstract:bC}],download_ids:"3890,4684,4755,5408,4913"},cited:[{article_id:cp,title:bn,image:e,tag:cq,doi:cr,date_published:cs,section:ct,authors:cu,journal_id:o,volume:h,year:q,section_id:e,special_name:a,url_doi:bm,pdf:cv,video_url:a,allauthors:"\u003Cimg src='https:\u002F\u002Fi.oaes.cc\u002Fimages\u002Fdefault_photo.png' class='author_photo' alt='Heba Taher'\u003E Heba Taher, \u003Cimg src='https:\u002F\u002Fi.oaes.cc\u002Fimages\u002Fdefault_photo.png' class='author_photo' alt='Vincent Grasso'\u003E Vincent Grasso, \u003Cimg src='https:\u002F\u002Fi.oaes.cc\u002Fimages\u002Fdefault_photo.png' class='author_photo' alt='Sherifa Tawfik'\u003E Sherifa Tawfik, \u003Cimg src='https:\u002F\u002Fi.oaes.cc\u002Fimages\u002Fdefault_photo.png' class='author_photo' alt='Andrew Gumbs'\u003E Andrew Gumbs",journal_path:k,video_img:a,image_list:e,abstract:cw},{article_id:bo,title:aC,image:D,tag:bp,doi:bq,date_published:br,section:u,authors:bs,journal_id:o,volume:h,year:q,section_id:e,special_name:a,url_doi:aB,pdf:bt,video_url:a,allauthors:cG,journal_path:k,video_img:a,image_list:D,abstract:bu},{article_id:bv,title:aE,image:E,tag:bw,doi:bx,date_published:by,section:bz,authors:bA,journal_id:o,volume:h,year:q,section_id:e,special_name:a,url_doi:aD,pdf:bB,video_url:a,allauthors:cH,journal_path:k,video_img:a,image_list:E,abstract:bC}],cited_ids:"5162,4684,4913"},indexFot:{webinars:[{id:bE,image:"https:\u002F\u002Fi.oaes.cc\u002Fuploads\u002F20241106\u002F0be7243ef2964546ac82ce4d7dab6e0e.jpg"}],osi:{url:"\u002Fspecials\u002Fais.1619",img:"https:\u002F\u002Fi.oaes.cc\u002Fuploads\u002F20230831\u002Fa178f81e557c4d44a8853e9287ca0e2d.jpg",list:[{section_id:2155,journal_id:t,deadline:1751342703,image:"https:\u002F\u002Fi.oaes.cc\u002Fuploads\u002F20240729\u002F31d3fd647e2049eea4ad7b74a685799d.jpg",sub_link:"https:\u002F\u002Foaemesas.com\u002Flogin?JournalId=ais&SpecialIssueId=ais240729",email:"AIS_editor@oaepublish.com",issue_flyer:a,title:"Topic: The Role of Artificial Intelligence in Neurosurgery",count:i,author:["Prof. Peter A. 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permanently:",url:"https:\u002F\u002Fwww.portico.org\u002Fpublishers\u002Foae\u002F",img:"https:\u002F\u002Fi.oaes.cc\u002Fuploads\u002F20230911\u002Fd59e360eb4a74bfea8426c0a1647c746.jpg"},follow:[{title:"LinkedIn",url:"https:\u002F\u002Fwww.linkedin.com\u002Fin\u002Fprofessor-andrew-a-gumbs-md-msc-ai-facs-he-him-003546201\u002F",icon:"icon-linkedin"},{title:"Twitter",url:kS,icon:"icon-tuite1"}],wechat_img:a,twitter:{url:kS,img:"https:\u002F\u002Fi.oaes.cc\u002Fuploads\u002F20230824\u002Fe16f23862a4a4904829b3e41ca3b43f9.png"}},top:{path:k,pid:t,journal_img:bW,journal_name:C,mpt:"55 days",issn:kR,indexing:{ESCI:ca,Scopus:aK,Dimensions:"https:\u002F\u002Fapp.dimensions.ai\u002Fdiscover\u002Fpublication?and_facet_source_title=jour.1410374",Lens:"https:\u002F\u002Fwww.lens.org\u002Flens\u002Fsearch\u002Fscholar\u002Flist?p=0&n=10&s=date_published&d=%2B&f=false&e=false&l=en&authorField=author&dateFilterField=publishedYear&orderBy=%2Bdate_published&presentation=false&preview=true&stemmed=true&useAuthorId=false&publicationType.must=journal%20article&sourceTitle.must=Artificial%20Intelligence%20Surgery&publisher.must=OAE%20Publishing%20Inc."},editor:aG,journal_rank:a,journal_flyer:a,qksearch:["Intelligence"],sitetag:"Art Int Surg",ad:[],colour_tag:bV,score:a,mobile_top_img:a,impact_factor:[{factor:bZ,url:aK},{factor:j,url:a}],rgba:bX,log_image:bY},webinfo:{},searchKey:a,loading:kT,appid:a,videoPlay:{show:aI,href:a}},editer:{editList:{list:{}}},userdata:{showLogin:aI,logined:aI}},serverRendered:kT,routePath:bR,config:{_app:{basePath:kU,assetsPath:kU,cdnURL:"https:\u002F\u002Fg.oaes.cc\u002Foae\u002Fnuxt\u002F"}}}}("",null,1,"2021","0",4,"1","2",0,"https:\u002F\u002Fi.oaes.cc\u002Fuploads\u002F20240506\u002Fea3d9071c35b4bf3982ffe25f1083620.png","ais",3,"3",2,"22","4","2022",5,"5",22,"Review","[]","6","https:\u002F\u002Fmjl.clarivate.com\u002Fsearch-results","2017",15,40,32,"Artificial Intelligence Surgery","https:\u002F\u002Fimage.oaes.cc\u002F2a947cb1-166c-4615-9509-319e78bd8e24\u002F4684-coverimg.jpg","https:\u002F\u002Fimage.oaes.cc\u002F312616a0-8551-4a62-a2b2-560ac4626634\u002F4913-coverimg.jpg",43,"Mini-invasive Surgery","Plastic and Aesthetic Research","33",10,20,"Lens",34,6,7,35,"2020","image","2024",9,84,490,294,39,13,31,14,"Extracellular Vesicles and Circulating Nucleic Acids","Microbiome Research Reports","One Health & Implementation Research","Chemical Synthesis","Energy Materials","Journal of Materials Informatics","Microstructures","Minerals and Mineral Materials","Soft Science","Complex Engineering Systems","Disaster Prevention and Resilience","Green Manufacturing Open","Intelligence & Robotics","Journal of Smart Environments and Green Computing","Journal of Surveillance, Security and Safety","Ageing and Neurodegenerative Diseases","Cancer Drug Resistance","Connected Health And Telemedicine","Hepatoma Research","Journal of Cancer Metastasis and Treatment","Journal of Translational Genetics and Genomics","Metabolism and Target Organ Damage","Rare Disease and Orphan Drugs Journal","The Journal of Cardiovascular Aging","Vessel Plus","Carbon Footprints","Journal of Environmental Exposure Assessment","Water Emerging Contaminants & Nanoplastics","ais.2021.15","Computer vision and machine learning for medical image analysis: recent advances, challenges, and way forward","ais.2022.10","White paper: definitions of artificial intelligence and autonomous actions in clinical surgery","https:\u002F\u002Fimage.oaes.cc\u002Ff63cb46b-2b81-4a36-84fc-a4ef999c3659\u002F4755-coverimg.jpg","Andrew A. Gumbs",1680307200,false,23,"https:\u002F\u002Fwww.scopus.com\u002Fsourceid\u002F21101189039",25,30,46,8,24,"ESCI, CAS, Dimensions, Lens, CNKI",17,11,55,12,"2015","ESCI, CAS, Scopus, Wanfang Data, CNKI, Dimensions, Embase","39",16,"Journal of Unexplored Medical Data",70,18,21,26,"ESCI, Scopus, CAS, Dimensions, Lens, CNKI","https:\u002F\u002Fi.oaes.cc\u002Fuploads\u002F20240809\u002Fccc8ac23b789404781787655e4495af4.png",33,"Neuroimmunology and Neuroinflammation","2014",29,"ISSN XXXX-XXXX (Coming soon)","Soil Health","Space Mission Planning & Operations","Stomatological Disease and Science","ais.2022.11","The challenges of deep learning in artificial intelligence and autonomous actions in surgery: a literature review","4684","24-45","10.20517\u002Fais.2021.15","1647878400","Eyad Elyan, ... Md. Mostafa Kamal Sarker","https:\u002F\u002Ff.oaes.cc\u002Fxmlpdf\u002F2a947cb1-166c-4615-9509-319e78bd8e24\u002F4684.pdf","\u003Cp\u003EThe recent development in the areas of deep learning and deep convolutional neural networks has significantly progressed and advanced the field of computer vision (CV) and image analysis and understanding. Complex tasks such as classifying and segmenting medical images and localising and recognising objects of interest have become much less challenging. This progress has the potential of accelerating research and deployment of multitudes of medical applications that utilise CV. However, in reality, there are limited practical examples being physically deployed into front-line health facilities. In this paper, we examine the current state of the art in CV as applied to the medical domain. We discuss the main challenges in CV and intelligent data-driven medical applications and suggest future directions to accelerate research, development, and deployment of CV applications in health practices. First, we critically review existing literature in the CV domain that addresses complex vision tasks, including: medical image classification; shape and object recognition from images; and medical segmentation. Second, we present an in-depth discussion of the various challenges that are considered barriers to accelerating research, development, and deployment of intelligent CV methods in real-life medical applications and hospitals. Finally, we conclude by discussing future directions.\u003C\u002Fp\u003E","4913","93-100","10.20517\u002Fais.2022.10","1654012800","Guideline","Andrew A. Gumbs\u003Ca href='https:\u002F\u002Forcid.org\u002F0000-0002-7044-5318' target='_blank'\u003E\u003Cimg src='https:\u002F\u002Fi.oaes.cc\u002Fimages\u002Forcid.png' class='author_id' alt='Andrew A. Gumbs'\u003E\u003C\u002Fa\u003E, ... Lee L. Swanström","https:\u002F\u002Ff.oaes.cc\u002Fxmlpdf\u002F312616a0-8551-4a62-a2b2-560ac4626634\u002F4913.pdf","\u003Cp\u003EThis white paper documents the consensus opinion of the expert members of the Editorial Board of Artificial Intelligence Surgery regarding the definitions of artificial intelligence and autonomy in regards to surgery and how the digital evolution of surgery is interrelated with the various forms of robotic-assisted surgery. It was derived from a series of video conference discussions, and the survey and results were subsequently revised and approved by all authors.\u003C\u002Fp\u003E","Topic: Role of Artificial Intelligence in HPB Surgery",296,"Abby_Editor@aisjournal.net","editorialoffice@aisjournal.net",42,78,"https:\u002F\u002Fi.oaes.cc\u002Fuploads\u002F20231110\u002Fa2ede06450eb4b0f9df7bef7efc9d60c.jpg","mis","Giulio Belli","https:\u002F\u002Fi.oaes.cc\u002Fuploads\u002F20231110\u002F8d72c3f669d5490ea3b9abc424d66cb6.jpg","par","Wen-Guo Cui",27,"Contact Us","\u002Fais","7","8","11","#030072","https:\u002F\u002Fi.oaes.cc\u002Fuploads\u002F20231110\u002F14bc775310574f91b457ff09d6c6d950.jpg","rgb(3,0,114)","https:\u002F\u002Fi.oaes.cc\u002Fupload\u002Fjournal_logo\u002Fais.png","https:\u002F\u002Fi.oaes.cc\u002Fuploads\u002F20240813\u002Fb7358d0632aa413fa84630ef0a2fb7a0.png","https:\u002F\u002Foaemesas.com\u002Flogin?JournalId=ais",1054,"https:\u002F\u002Fwww.oaepublish.com\u002Fnews\u002Fais.847","https:\u002F\u002Fv.oaes.cc\u002Fuploads\u002F20241105\u002F049625faa328464a8b1fbbc2eb24f3c4.mp4","1850","Topic: Elevating Spine Surgery with AI: Current Landscape and Future Frontiers","1952","Topic: Role of AI in Plastic and Reconstructive Surgery","3890","What is Artificial Intelligence Surgery?","1-10","10.20517\u002Fais.2021.01","1611936000","Editorial","Andrew A. Gumbs, ... Elie Chouillard","ais.2021.01","https:\u002F\u002Ff.oaes.cc\u002Fxmlpdf\u002F12698bfb-9a4f-4399-9885-6955f9c3d8de\u002F3890.pdf","5162","144-58","10.20517\u002Fais.2022.11","1663862400","Systematic Review","Heba Taher, ... Andrew Gumbs","https:\u002F\u002Ff.oaes.cc\u002Fxmlpdf\u002F40a569c1-4db5-4986-ac38-bf3907959d45\u002F5162.pdf","\u003Cp\u003E\u003Cb\u003EAim: \u003C\u002Fb\u003EArtificial intelligence (AI) is rapidly evolving in healthcare worldwide, especially in surgery. This article reviews important terms used in machine learning and the challenges of deep learning in surgery.\u003C\u002Fp\u003E\u003Cp\u003E\u003Cb\u003EMethods:\u003C\u002Fb\u003E A review of the English literature was carried out focused on the terms “challenges of deep learning” and “surgery” using Medline and PubMed between 2018 and 2022.\u003C\u002Fp\u003E\u003Cp\u003E\u003Cb\u003EResults:\u003C\u002Fb\u003E In total, 54 articles discussed the challenges of deep learning in general. We include 25 articles from various surgical specialties discussing challenges corresponding to their respective specialties.\u003C\u002Fp\u003E\u003Cp\u003E\u003Cb\u003EConclusion: \u003C\u002Fb\u003EThe increased utilization of AI in surgery is faced with a wide variety of technical, ethical, clinical, and business-related challenges. The best way to expedite its expansion in surgery in the safest and most cost-efficient manner is by ensuring that as many surgeons as possible have a clear understanding of basic AI concepts and how they can be applied to the preoperative, intraoperative, postoperative, and long-term follow-up phases of the surgical patient care.\u003C\u002Fp\u003E","4755","The importance of machine learning in autonomous actions for surgical decision making","64-79","10.20517\u002Fais.2022.02","1650211200","Martin Wagner\u003Ca href='https:\u002F\u002Forcid.org\u002F0000-0002-9831-9110' target='_blank'\u003E\u003Cimg src='https:\u002F\u002Fi.oaes.cc\u002Fimages\u002Forcid.png' class='author_id' alt='Martin Wagner'\u003E\u003C\u002Fa\u003E, ... Stefanie Speidel\u003Ca href='https:\u002F\u002Forcid.org\u002F0000-0002-4590-1908' target='_blank'\u003E\u003Cimg src='https:\u002F\u002Fi.oaes.cc\u002Fimages\u002Forcid.png' class='author_id' alt='Stefanie Speidel'\u003E\u003C\u002Fa\u003E","ais.2022.02","https:\u002F\u002Ff.oaes.cc\u002Fxmlpdf\u002Ff63cb46b-2b81-4a36-84fc-a4ef999c3659\u002F4755.pdf","\u003Cp\u003ESurgery faces a paradigm shift since it has developed rapidly in recent decades, becoming a high-tech discipline. Increasingly powerful technological developments such as modern operating rooms, featuring digital and interconnected equipment and novel imaging as well as robotic procedures, provide several data sources resulting in a huge potential to improve patient therapy and surgical outcome by means of Surgical Data Science. The emerging field of Surgical Data Science aims to improve the quality of surgery through acquisition, organization, analysis, and modeling of data, in particular using machine learning (ML). An integral part of surgical data science is to analyze the available data along the surgical treatment path and provide a context-aware autonomous action by means of ML methods. Autonomous actions related to surgical decision-making include preoperative decision support, intraoperative assistance functions, as well as robot-assisted actions. The goal is to democratize surgical skills and enhance the collaboration between surgeons and cyber-physical systems by quantifying surgical experience and making it accessible to machines, thereby improving patient therapy and outcome. The article introduces basic ML concepts as enablers for autonomous actions in surgery, highlighting examples for such actions along the surgical treatment path.\u003C\u002Fp\u003E","\u003Cimg src='https:\u002F\u002Fi.oaes.cc\u002Fimages\u002Fdefault_photo.png' class='author_photo' alt='Eyad Elyan'\u003E Eyad Elyan, \u003Cimg src='https:\u002F\u002Fi.oaes.cc\u002Fimages\u002Fdefault_photo.png' class='author_photo' alt='Pattaramon Vuttipittayamongkol'\u003E Pattaramon Vuttipittayamongkol, \u003Cimg src='https:\u002F\u002Fi.oaes.cc\u002Fimages\u002Fdefault_photo.png' class='author_photo' alt='Pamela Johnston'\u003E Pamela Johnston, \u003Cimg src='https:\u002F\u002Fi.oaes.cc\u002Fimages\u002Fdefault_photo.png' class='author_photo' alt='Kyle Martin'\u003E Kyle Martin, \u003Cimg src='https:\u002F\u002Fi.oaes.cc\u002Fimages\u002Fdefault_photo.png' class='author_photo' alt='Kyle McPherson'\u003E Kyle McPherson, \u003Cimg src='https:\u002F\u002Fi.oaes.cc\u002Fimages\u002Fdefault_photo.png' class='author_photo' alt='Carlos Francisco Moreno-García'\u003E Carlos Francisco Moreno-García, \u003Cimg src='https:\u002F\u002Fi.oaes.cc\u002Fimages\u002Fdefault_photo.png' class='author_photo' alt='Chrisina Jayne'\u003E Chrisina Jayne, \u003Cimg src='https:\u002F\u002Fi.oaes.cc\u002Fimages\u002Fdefault_photo.png' class='author_photo' alt='Md. Mostafa Kamal Sarker'\u003E Md. Mostafa Kamal Sarker","\u003Cimg src='https:\u002F\u002Fi.oaes.cc\u002Fimages\u002Fdefault_photo.png' class='author_photo' alt='Andrew A. Gumbs'\u003E Andrew A. Gumbs\u003Ca href='https:\u002F\u002Forcid.org\u002F0000-0002-7044-5318' target='_blank'\u003E\u003Cimg src='https:\u002F\u002Fi.oaes.cc\u002Fimages\u002Forcid.png' class='author_id' alt='Andrew A. Gumbs'\u003E\u003C\u002Fa\u003E, \u003Cimg src='https:\u002F\u002Fi.oaes.cc\u002Fimages\u002Fdefault_photo.png' class='author_photo' alt='Frank Alexander'\u003E Frank Alexander, \u003Cimg src='https:\u002F\u002Fi.oaes.cc\u002Fimages\u002Fdefault_photo.png' class='author_photo' alt='Konrad Karcz'\u003E Konrad Karcz\u003Ca href='https:\u002F\u002Forcid.org\u002F0000-0002-4711-3630' target='_blank'\u003E\u003Cimg src='https:\u002F\u002Fi.oaes.cc\u002Fimages\u002Forcid.png' class='author_id' alt='Konrad Karcz'\u003E\u003C\u002Fa\u003E, \u003Cimg src='https:\u002F\u002Fi.oaes.cc\u002Fimages\u002Fdefault_photo.png' class='author_photo' alt='Elie Chouillard'\u003E Elie Chouillard\u003Ca href='https:\u002F\u002Forcid.org\u002F0000-0003-4100-7412' target='_blank'\u003E\u003Cimg src='https:\u002F\u002Fi.oaes.cc\u002Fimages\u002Forcid.png' class='author_id' alt='Elie Chouillard'\u003E\u003C\u002Fa\u003E, \u003Cimg src='https:\u002F\u002Fi.oaes.cc\u002Fimages\u002Fdefault_photo.png' class='author_photo' alt='Roland Croner'\u003E Roland Croner\u003Ca href='https:\u002F\u002Forcid.org\u002F0000-0001-6248-7086' target='_blank'\u003E\u003Cimg src='https:\u002F\u002Fi.oaes.cc\u002Fimages\u002Forcid.png' class='author_id' alt='Roland Croner'\u003E\u003C\u002Fa\u003E, \u003Cimg src='https:\u002F\u002Fi.oaes.cc\u002Fimages\u002Fdefault_photo.png' class='author_photo' alt='Jasamine Coles-Black'\u003E Jasamine Coles-Black, \u003Cimg src='https:\u002F\u002Fi.oaes.cc\u002Fimages\u002Fdefault_photo.png' class='author_photo' alt='Belinda de Simone'\u003E Belinda de Simone\u003Ca href='https:\u002F\u002Forcid.org\u002F0000-0002-7956-3097' target='_blank'\u003E\u003Cimg src='https:\u002F\u002Fi.oaes.cc\u002Fimages\u002Forcid.png' class='author_id' alt='Belinda de Simone'\u003E\u003C\u002Fa\u003E, \u003Cimg src='https:\u002F\u002Fi.oaes.cc\u002Fimages\u002Fdefault_photo.png' class='author_photo' alt='Michel Gagner'\u003E Michel Gagner\u003Ca href='https:\u002F\u002Forcid.org\u002F0000-0001-6068-0333' target='_blank'\u003E\u003Cimg src='https:\u002F\u002Fi.oaes.cc\u002Fimages\u002Forcid.png' class='author_id' alt='Michel Gagner'\u003E\u003C\u002Fa\u003E, ... \u003Cimg src='https:\u002F\u002Fi.oaes.cc\u002Fimages\u002Fdefault_photo.png' class='author_photo' alt='Lee L. Swanström'\u003E Lee L. Swanström",991,"https:\u002F\u002Fi.oaes.cc\u002Fpublic\u002Fissue_special\u002F991\u002F98_ais_sp991.jpg","Topic: Women in Surgery Meets \u003Cem\u003EAIS\u003C\u002Fem\u003E Journal",1105,"https:\u002F\u002Fi.oaes.cc\u002Fpublic\u002Fissue_special\u002F1105\u002F48_ais_sp1105.jpg","About","Editorial Policies","Journals","Biology & Life Science","Chemistry & Materials Science","Computer Science & Engineering","Medicine & Public Health","9","10","Environmental Science","#837fbc","ISSN 2769-5301 (Online)","https:\u002F\u002Fi.oaes.cc\u002Fuploads\u002F20231218\u002F6135b005a8674b878a7d1a5c91ac9869.jpg","https:\u002F\u002Fwww.oaepublish.com\u002Fand","Wei-Dong Le","CAS, Dimensions, Lens, CNKI","rgb(99,94,171)","https:\u002F\u002Fi.oaes.cc\u002Fupload\u002Fjournal_logo\u002Fand.jpg","and",66,"ISSN 2771-0408 (Online)","https:\u002F\u002Fwww.oaepublish.com\u002Fais","36","ESCI, Scopus, Dimensions, Lens","#e8b475","ISSN 2578-532X (Online)","https:\u002F\u002Fi.oaes.cc\u002Fuploads\u002F20231113\u002F9db4b73f2e954900807499f00094fcf0.jpg","https:\u002F\u002Fwww.oaepublish.com\u002Fcdr","Godefridus J. (Frits) Peters","2018","337","ESCI, PMC, Scopus, CAS, CNKI, Dimensions, Lens, Embase","rgb(224,155,71)","https:\u002F\u002Fi.oaes.cc\u002Fupload\u002Fjournal_logo\u002Fcdr.jpg","https:\u002F\u002Fi.oaes.cc\u002Fuploads\u002F20240104\u002F502e35965fc448e0bc9f2d6c1b0bb3d7.png","https:\u002F\u002Fwww.ncbi.nlm.nih.gov\u002Fpmc\u002Fjournals\u002F4180\u002F","https:\u002F\u002Fi.oaes.cc\u002Fuploads\u002F20240611\u002F5def3ab5829743ce8d55e664cabe0dcb.png","https:\u002F\u002Fwww.scopus.com\u002Fsourceid\u002F21101047803","https:\u002F\u002Fi.oaes.cc\u002Fuploads\u002F20240620\u002Fed79fcbfce8e4cd38a36cc4d5f7d473d.png","https:\u002F\u002Fjcr.clarivate.com\u002Fjcr-jp\u002Fjournal-profile?journal=CANCER%20DRUG%20RESIST&year=2022","https:\u002F\u002Fi.oaes.cc\u002Fuploads\u002F20240620\u002F86311aafb7a945a98a7ee95c3627173b.png","cdr",418,38,"#1d57a5","ISSN 2770-6249 (Online)","https:\u002F\u002Fi.oaes.cc\u002Fimages_2018\u002Foae\u002Fcover_comengsys.jpg","https:\u002F\u002Fwww.oaepublish.com\u002Fcomengsys","Hamid Reza Karimi","37","Scopus, Dimensions, Lens","rgb(29,87,165)","https:\u002F\u002Fi.oaes.cc\u002Fupload\u002Fjournal_logo\u002Fces.png","https:\u002F\u002Fi.oaes.cc\u002Fuploads\u002F20240722\u002F4748814aab87441d809e5b9ddcd9d56e.png","https:\u002F\u002Fwww.scopus.com\u002Fsourceid\u002F21101189038","comengsys",74,58,"#75ac9d","ISSN 2993-2920 (Online)","https:\u002F\u002Fi.oaes.cc\u002Fuploads\u002F20231218\u002F0b7a80c0f6e545818e143ea48fe9be90.jpg","https:\u002F\u002Fwww.oaepublish.com\u002Fchatmed","Yuan-Ting Zhang","20","rgb(117, 172, 157)","https:\u002F\u002Fi.oaes.cc\u002Fupload\u002Fjournal_logo\u002Fchatmed.jpg","chatmed","#00a5b3","ISSN 2769-5247 (Online)","https:\u002F\u002Fi.oaes.cc\u002Fuploads\u002F20231121\u002F1598f33bf2284642830511e489eb31bf.jpg","https:\u002F\u002Fwww.oaepublish.com\u002Fcs","Bao-Lian Su","67","Scopus, 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Dimensions","rgb(41,167,168)","https:\u002F\u002Fi.oaes.cc\u002Fupload\u002Fjournal_logo\u002Fmis.jpg","https:\u002F\u002Fi.oaes.cc\u002Fuploads\u002F20240208\u002F6020c4a092dd44578a776056b5057abc.png","https:\u002F\u002Fwww.scopus.com\u002Fsourceid\u002F21101115668",397,"#33a7d9","ISSN 2349-6142 (Online)\u003Cbr\u003EISSN 2347-8659 (Print)","https:\u002F\u002Fi.oaes.cc\u002Fuploads\u002F20231110\u002F026484b9f2b042fda9b7afffc0d9f62e.jpg","https:\u002F\u002Fwww.oaepublish.com\u002Fneurosciences","296","rgb(51,167,217)","https:\u002F\u002Fi.oaes.cc\u002Fupload\u002Fjournal_logo\u002Fnn.jpg",104,"neurosciences",28,"#43b02a","ISSN 2769-6413 (Online)","https:\u002F\u002Fi.oaes.cc\u002Fuploads\u002F20231110\u002Ff65f06a7eae24d1484bad38ff0a2bef2.jpg","https:\u002F\u002Fwww.oaepublish.com\u002Fohir","25","Dimensions","Jose M. Martin-Moreno","rgb(67,176,42)","https:\u002F\u002Fi.oaes.cc\u002Fupload\u002Fjournal_logo\u002Fohir.jpg",105,"ohir","#c45284","ISSN 2349-6150 (Online)\u003Cbr\u003EISSN 2347-9264 (Print)","https:\u002F\u002Fwww.oaepublish.com\u002Fpar","520","rgb(196,82,132)","ESCI, Scopus, Dimensions, CNKI, Lens, Wanfang","https:\u002F\u002Fi.oaes.cc\u002Fupload\u002Fjournal_logo\u002Fpar.jpg","https:\u002F\u002Fi.oaes.cc\u002Fuploads\u002F20240607\u002F9bbbcad710cf457e85d63b1811faefb1.png","https:\u002F\u002Fwww.scopus.com\u002Fsourceid\u002F21101111784","https:\u002F\u002Fclarivate.com\u002Fproducts\u002Fscientific-and-academic-research\u002Fresearch-discovery-and-workflow-solutions\u002Fwebofscience-platform\u002Fweb-of-science-core-collection\u002Femerging-sources-citation-index\u002F",622,"#d62598","ISSN 2771-2893 (Online)","https:\u002F\u002Fi.oaes.cc\u002Fuploads\u002F20231121\u002F6ee75e8ab583446b90c97865c2c68464.jpg","https:\u002F\u002Fwww.oaepublish.com\u002Frdodj","Daniel Scherman","28","Dimensions, Lens","rgb(214,37,152)","https:\u002F\u002Fi.oaes.cc\u002Fupload\u002Fjournal_logo\u002Frdodj.jpg",106,"rdodj","#1f4e79","ISSN 2769-5441 (Online)","https:\u002F\u002Fi.oaes.cc\u002Fuploads\u002F20231110\u002F98e2ed5023ee466c8890d749bfd97597.jpg","https:\u002F\u002Fwww.oaepublish.com\u002Fss","YongAn Huang","58","ESCI, Scopus, CAS, Lens, Dimensions, CNKI","rgb(31,78,121)","https:\u002F\u002Fi.oaes.cc\u002Fupload\u002Fjournal_logo\u002Fss.jpg",107,"https:\u002F\u002Fi.oaes.cc\u002Fuploads\u002F20240606\u002Fcfa200290630438c8e3a3cae1536af37.png","https:\u002F\u002Fwww.scopus.com\u002Fsourceid\u002F21101178114","ss",120,54,"#a96318","https:\u002F\u002Fi.oaes.cc\u002Fimages_2018\u002Foae\u002Fcover_sh.jpg","https:\u002F\u002Fwww.oaepublish.com\u002Fsh","Manoj Shukla","rgb(169,99,24)","https:\u002F\u002Fi.oaes.cc\u002Fupload\u002Fjournal_logo\u002Fsh.jpg",108,"sh","#4475e1","https:\u002F\u002Fi.oaes.cc\u002Fuploads\u002F20231218\u002F79ccda0bc909441587a0b70e0a8ef1cc.jpg","https:\u002F\u002Fwww.oaepublish.com\u002Fsmpo","Madjid Tavana","rgb(68,117,225)","https:\u002F\u002Fi.oaes.cc\u002Fupload\u002Fjournal_logo\u002Fsmpo.jpg",109,"smpo","#53be9b","ISSN 2573-0002 (Online)","https:\u002F\u002Fi.oaes.cc\u002Fuploads\u002F20231218\u002F54ba11ec5c57448a84169c318bb94fd4.jpg","https:\u002F\u002Fwww.oaepublish.com\u002Fsds","Nikolaos G. 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