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AI Imaging & Diagnostics – Google Health
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glue-mod-spacer-3-bottom"> <a class="menu-link" href="../../health-research/publications/" aria-label="Publications"> Publications </a> </p> </div> </div> </div> <div class="backdrop"></div> </div> </li> <li class="glue-header__item" aria-level="1"> <div> <div class="header-navlist"> <a href="../../partners/" class="glue-header__link our-partners" aria-label="Where we're giving"> Where we're giving </a> </div> </div> </li> </ul> </nav> </div> </div> </div> <div class="glue-header__drawer-backdrop"></div> </header> <main class="g-h-main g-h-main--imaging-and-diagnostics"> <div class="g-h-health__wrapper imaging-and-diagnostics-hero"> <section class="g-h-block-style"> <div class="glue-grid g-health-hero"> <div class="glue-grid__col glue-grid__col--span-6 glue-grid__col--span-12-md glue-mod-order-2-md glue-mod-order-2-sm glue-mod-order-1"> <div class="g-health-hero__content"> <h1 class="glue-headline glue-headline--headline-1"> AI-enabled imaging and diagnostics previously thought impossible </h1> <div class="g-h-markdown glue-body"> <p>In partnership with healthcare organisations globally, we’re researching robust new AI-enabled tools focused on diagnostics to assist clinicians. Drawing from diverse datasets, high-quality labels and state-of-the-art deep learning techniques, we are making models that we hope will eventually support medical specialists in diagnosing disease. We’re excited to further develop this research towards new frontiers – and to demonstrate that AI has the ability to enable novel, transformative diagnostics.</p> </div> </div> </div> <div class="glue-grid__col glue-grid__col--span-6 glue-grid__col--span-12-md glue-mod-order-1-md g-h-landing-hero_image"> <img src="https://lh3.googleusercontent.com/E6t2_DmkNYyqxiTM0-5302hp4rx--PAJkarLWWDTdf4WZWaYkXyKghriee-dR7m6hW0yf3NwvrnsR9soDKdLpcyO-bpw8Ul1MHpRIiP0KMbUhPCmDLQ=w1100" alt="Mother and daughter embracing"> </div> </div> </section></div> <section class="g-h-block-style glue-mod-spacer-0-bottom" id="dermatology"> <div class="g-h-health__wrapper"> <div class="g-h-text-slider-headline g-h-text-slider-4-headline glue-mod-text-center glue-grid__col--span-12 dermatology-mobile-section"> <h2 class="glue-headline glue-headline--headline-3 glue-mod-spacer-4-bottom"> Improving access to skin disease information</h2> </div> <div class="g-h-dermatology-section"> <div class="g-h-content-block g-h-video-caption"> <div class="glue-grid content-block-grid"> <div class="glue-grid__col glue-grid__col--span-12-md glue-grid__col--align-middle glue-grid__col--span-6 glue-mod-order-1 glue-mod-order-1-md"> <div class="g-h-content-block__asset"> <div class="g-h-html-video"> <video id="video-mp4" class="g-h-html-video__player" autoplay muted playsinline loop> <source src="https://kstatic.googleusercontent.com/files/92ab9294c42476d0ffc2c8733aa601a55a9f74ad66a8920e2be06e6cddb1d672a093045c6772eea05eedabbfb7a3f6c355d37e4198e5e94d0187a7dc62f2a182" type="video/mp4"> </video> </div> <p class="glue-small-text glue-mod-spacer-2-top glue-mod-text-left g-h-video-caption">This product has been CE marked as a Class I medical device in the EU. It is not available in the United States. This research is not related to the DermAssist tool, which is no longer in development.</p> </div> </div> <div class="g-h__desc-section glue-grid__col glue-grid__col--align-middle glue-grid__col--span-6 glue-grid__col--span-12-md glue-mod-order-2 glue-mod-order-2-md"> <div class="g-h-content-block__title glue-mod-spacer-3-bottom"> <h2 class="glue-headline glue-headline--headline-3">Improving access to skin disease information</h2> </div> <div class="g-h-content-block__text"> <p>Through computer vision AI and image search capabilities, we are developing a tool to help individuals better research and identify their skin, hair and nail conditions. The tool supports hundreds of conditions, including more than 80% of the conditions seen in clinics and more than 90% of the most commonly searched conditions. The work was highlighted in both <a href="https://www.nature.com/articles/s41591-020-0842-3">Nature Medicine</a> and <a href="https://jamanetwork.com/journals/jamanetworkopen/fullarticle/2779250">JAMA Network Open</a>. <a href="/consumers/dermassist/">Learn more</a></p> </div> <div class="g-h-content-block__cta glue-mod-spacer-3-top"> </div> </div> </div> </div> </div> </div> </div> </section><section class="g-h-block-style"> <div class="glue-page g-h-health__wrapper g-h-imaging-diagnostics__content-section"> <div class="g-h-text-slider-headline g-h-text-slider-4-headline glue-mod-text-center glue-grid__col--span-12"> <h2 class="glue-headline glue-headline--headline-3 glue-mod-spacer-4-bottom"> Using AI to help doctors address eye disease</h2> </div> <div class="g-h-content-block g-h-content-block--text-slider"> <div class="glue-grid content-block-grid"> <div class="glue-grid__col glue-grid__col--span-12-md glue-grid__col--align-middle glue-grid__col--span-6 glue-mod-order-1 glue-mod-order-2-md glue-mod-order-2-lg glue-mod-order-2-xl"> <div class="g-h-content-block__asset g-h-content-block__asset--reverse"> <div class="g-h-html-video"> <video id="video-mp4" class="g-h-html-video__player" autoplay muted playsinline loop> <source src="https://kstatic.googleusercontent.com/files/c24d2dc40ac70f4d5f7aa0d633210c8f5d85f21e721ac183936aab0d794a0ee83163cd7cb08f8e09c13793b4338d57adc71d19139f512306d3f3224594391168" type="video/mp4"> </video> </div> </div> </div> <div class="g-h__desc-section glue-grid__col glue-grid__col--align-middle glue-grid__col--span-6 glue-grid__col--span-12-md glue-mod-order-2 glue-mod-order-1-md glue-mod-order-1-lg glue-mod-order-1-xl"> <div class="g-h-content-block__title glue-mod-spacer-3-bottom"> <h2 class="glue-headline glue-headline--headline-3">Helping doctors prevent blindness</h2> </div> <div class="g-h-content-block__text"> <p><a href="../../../../caregivers/arda/">Automated Retinal Disease Assessment (ARDA)</a> is being used to help clinicians detect diabetic retinopathy, a leading cause of blindness, in India and across the world. With widespread adoption, millions of patients with diabetes could keep their vision thanks in part to ARDA assisting doctors. Our research was published in <a href="https://jamanetwork.com/journals/jama/fullarticle/2588763">JAMA</a> and <a href="https://www.aaojournal.org/article/S0161-6420(17)32698-2/fulltext">Ophthalmology</a>. Additional research, published in <a href="https://www.thelancet.com/journals/landig/article/PIIS2589-7500(20)30250-8/fulltext">The Lancet Digital Health</a>, showed that we can predict whether patients will develop diabetic retinopathy in the future, which can help doctors customise both treatment and eye screening frequencies for their patients. The solution is currently being evaluated in clinical studies in the United States as well as in Thailand. <a href="../../../../caregivers/arda/">Learn more</a>.</p> </div> </div> </div> </div> </div> </section> <div class="g-h-swoop g-h-swoop--imaging-swoop-2"> <svg xmlns="http://www.w3.org/2000/svg" class="g-h-swoop-image" width="493.472" height="697.079" viewBox="0 0 493.472 697.079"><path d="M492.674 607.724s-309.972 81.753-371.992-78.773C60.34 372.77 147.953 209.752 329.975.902" fill="none" stroke="#34a953" stroke-miterlimit="10" stroke-width="2.00024"/></svg> </div> <section class="g-h-block-style glue-mod-spacer-0-bottom" id="lung-cancer-detection"> <div class="glue-page g-h-health__wrapper g-h-imaging-diagnostics__content-section"> <div class="g-h-text-slider-headline g-h-text-slider-4-headline glue-mod-text-center glue-grid__col--span-12"> <h2 class="glue-headline glue-headline--headline-3 glue-mod-spacer-4-bottom"> Using AI to improve lung cancer detection</h2> </div> <div class="g-h-content-block g-h-content-block--text-slider"> <div class="glue-grid content-block-grid"> <div class="glue-grid__col glue-grid__col--span-12-md glue-grid__col--align-middle glue-grid__col--span-6 glue-mod-order-1 glue-mod-order-1-md"> <div class="g-h-content-block__asset"> <div class="g-h-html-video"> <video id="video-mp4" class="g-h-html-video__player" autoplay muted playsinline loop> <source src="https://kstatic.googleusercontent.com/files/0279f88da7b25f93082e78b45a875444d8400afaf8f5bbdebaab1212a053b524e213bd40ae1fea7b5d8129a8cc0709159b9ec8f39a78aafb84ae6c5549c88720" type="video/mp4"> </video> </div> </div> </div> <div class="g-h__desc-section glue-grid__col glue-grid__col--align-middle glue-grid__col--span-6 glue-grid__col--span-12-md glue-mod-order-2 glue-mod-order-2-md"> <div class="g-h-content-block__title glue-mod-spacer-3-bottom"> <h2 class="glue-headline glue-headline--headline-3">A promising step forward for predicting lung cancer</h2> </div> <div class="g-h-content-block__text"> <p>Lung cancer leads to over 1.8 million deaths per year worldwide, accounting for almost one in five cancer deaths, and is the largest cause of cancer mortality. Our research, published in <a href="https://www.nature.com/articles/s41591-019-0447-x">Nature Medicine</a>, shows that deep learning may eventually help physicians more accurately screen for lung cancer and identify the disease even in incidental lung cancer detection workflows. <a href="https://blog.google/technology/health/lung-cancer-prediction/">Read the post</a></p> </div> </div> </div> </div> </div> </section> <div class="glue-page g-h-health__wrapper"> <div class="glue-grid"> <div class="g-h-text-slider-headline glue-mod-text-center glue-grid__col--span-12"> <h2 class="glue-headline glue-headline--headline-3 glue-mod-spacer-3-bottom"> Novel biomarkers for non-eye-related conditions</h2> </div> <div class="glue-grid__col glue-grid__col--span-12-md glue-grid__col--align-middle glue-grid__col--span-5 glue-mod-order-3-sm glue-mod-order-1-lg g-h-health_tab-align"> <div class="g-h-health-tabpanels glue-page"> <div class="glue-tabpanels glue-tabpanels--centeredtabs g-health-tabpanels-responsive" data-glue-tabpanels="tabs-noicons"> <div class="glue-tabpanels__page-list"> <div><p class="g-h-health-tab-title">Anemia Detection</p></div> <div><p class="g-h-health-tab-title">Computer Vision</p></div> </div> <div class="glue-tabpanels__panel-list" data-glue-expansion-panels-key="imaging-panel-two"> <div id="tab-item-1-imaging-panel-two"> <div class="glue-tabpanels__panel-title"> <h2> Anemia Detection </h2> <svg role="presentation" aria-hidden="true" class="glue-icon glue-expansion-panel__button-arrow"> <use xlink:href="/static/img/glue-icons.svg#expand-more"></use> </svg> </div> <div id="tab-item-1-imaging-panel-two-content" class="glue-tabpanels__panel-content"> <div> <h3 class="glue-headline glue-headline--headline-4 glue-mod-spacer-2-bottom">Detecting hidden signs of anaemia from the eye</h3> <p><div class="g-h-markdown glue-body"> <p>The human eye can reveal signs of underlying diseases like anaemia, a condition that affects 1.6 billion people worldwide causing tiredness, weakness, dizziness and drowsiness. In research published in <a href="https://www.nature.com/articles/s41551-019-0487-z">Nature Biomedical Engineering</a>, we were able to use deep learning to quantify haemoglobin levels and detect anaemia with de-identified photographs of the back of the eye. This result means that it’s possible that someday providers may be able to detect the disease with a simple non-invasive screening tool. <a href="https://www.blog.google/technology/health/anemia-detection-retina/">Read the post</a></p> </div> </p> </div> </div> </div> <div id="tab-item-2-imaging-panel-two"> <div class="glue-tabpanels__panel-title"> <h2> Computer Vision </h2> <svg role="presentation" aria-hidden="true" class="glue-icon glue-expansion-panel__button-arrow"> <use xlink:href="/static/img/glue-icons.svg#expand-more"></use> </svg> </div> <div id="tab-item-2-imaging-panel-two-content" class="glue-tabpanels__panel-content"> <div> <h3 class="glue-headline glue-headline--headline-4 glue-mod-spacer-2-bottom">Using computer vision to assess cardiovascular risk</h3> <p><div class="g-h-markdown glue-body"> <p>Assessing the risk of cardiovascular diseases is the first and most critical step towards reducing the likelihood that a patient suffers a cardiovascular event in the future. By applying deep learning techniques to retinal images, we’ve been able to reveal factors associated with the risk of a major cardiovascular event like a heart attack or stroke, as published in <a href="https://www.nature.com/articles/s41551-018-0195-0">Nature Biomedical Engineering</a>. This research could help scientists generate more targeted hypotheses and drive a wide range of future research. <a href="https://ai.googleblog.com/2018/02/assessing-cardiovascular-risk-factors.html">Read the post</a></p> </div> </p> </div> </div> </div> </div> </div> </div> </div> <div class="glue-grid__col glue-grid__col--span-12-md glue-grid__col--align-middle glue-grid__col--span-1 glue-mod-order-2-sm glue-mod-order-2-lg"></div> <div class="glue-grid__col glue-grid__col--span-12-md glue-grid__col--align-middle glue-grid__col--span-6 glue-mod-order-1-sm glue-mod-order-3-lg"> <div class="g-h-html-video glue-mod-spacer-6-top"> <video id="video-mp4" class="g-h-html-video__player" autoplay muted playsinline loop> <source src="https://kstatic.googleusercontent.com/files/e6167652b3ad902a57f14e405e487e852173d1fde27a3a87a5fce53ba237559e0a5b36965fe6082d6e99fa36945e96ac1ec09c6be49024753523482fa0df55c2" type="video/mp4"> </video> </div> </div> </div> </div> <div class="glue-page g-h-health__wrapper"> <div class="glue-grid"> <div class="g-h-text-slider-headline g-h-text-slider-4-headline glue-mod-text-center glue-grid__col--span-12"> <h2 class="glue-headline glue-headline--headline-3 glue-mod-spacer-4-bottom">Using AI to improve breast cancer detection</h2> </div> <div class="glue-grid__col glue-grid__col--span-12-md glue-grid__col--align-middle glue-grid__col--span-6"> <div class="g-h-html-video glue-mod-spacer-6-top"> <video id="video-mp4" class="g-h-html-video__player" autoplay muted playsinline loop> <source src="https://kstatic.googleusercontent.com/files/3d9c2f23ebfbec301e0b63bf250e520ee5fa8c01abefc940aeff9bc1191e0ff7d0be1f266becccb5c92e6ec4236ed27fa28ace3ea174d5d6bdd83c02c35cbfcb" type="video/mp4"> </video> </div> </div> <div class="glue-grid__col glue-grid__col--span-12-md glue-grid__col--align-middle glue-grid__col--span-1"></div> <div class="glue-grid__col glue-grid__col--span-12-md glue-grid__col--align-middle glue-grid__col--span-5 g-h-health_tab-align"> <div class="g-h-health-tabpanels glue-page"> <div class="glue-tabpanels glue-tabpanels--centeredtabs g-health-tabpanels-responsive" data-glue-tabpanels="tabs-noicons"> <div class="glue-tabpanels__page-list"> <div><p class="g-h-health-tab-title">Clinical Practice</p></div> <div><p class="g-h-health-tab-title">Deep Learning</p></div> </div> <div class="glue-tabpanels__panel-list" data-glue-expansion-panels-key="imaging-panel-three"> <div id="tab-item-1-imaging-panel-three"> <div class="glue-tabpanels__panel-title"> <h2> Clinical Practice </h2> <svg role="presentation" aria-hidden="true" class="glue-icon glue-expansion-panel__button-arrow"> <use xlink:href="/static/img/glue-icons.svg#expand-more"></use> </svg> </div> <div id="tab-item-1-imaging-panel-three-content" class="glue-tabpanels__panel-content"> <div> <h3 class="glue-headline glue-headline--headline-4 glue-mod-spacer-2-bottom">Studying how AI can help breast cancer screening in clinical practice</h3> <p><div class="g-h-markdown glue-body"> <p>Breast cancer screening helps detect cancer earlier, but diagnosing breast cancer accurately and consistently remains a challenge, with half of all women experiencing a false positive over a 10-year period. In <a href="https://www.nature.com/articles/s41586-019-1799-6">Nature</a>, we demonstrated the potential of our AI model to analyse de-identified retrospectively collected screening mammograms with similar or better accuracy than clinicians. Now, we’re collaborating on an investigative device research study to understand how the model can help in clinical practice to reduce the time from screening mammography to diagnosis, narrowing the assessment gap and improving the patient experience. <a href="https://blog.google/technology/health/artificial-intelligence-breast-cancer-screening/">Read the post</a></p> </div> </p> </div> </div> </div> <div id="tab-item-2-imaging-panel-three"> <div class="glue-tabpanels__panel-title"> <h2> Deep Learning </h2> <svg role="presentation" aria-hidden="true" class="glue-icon glue-expansion-panel__button-arrow"> <use xlink:href="/static/img/glue-icons.svg#expand-more"></use> </svg> </div> <div id="tab-item-2-imaging-panel-three-content" class="glue-tabpanels__panel-content"> <div> <h3 class="glue-headline glue-headline--headline-4 glue-mod-spacer-2-bottom">Applying deep learning to metastatic breast cancer detection</h3> <p><div class="g-h-markdown glue-body"> <p>In our pathology research published in the <a href="https://meridian.allenpress.com/aplm/article/143/7/859/10038/Artificial-Intelligence-Based-Breast-Cancer-Nodal">Archives of Pathology & Laboratory Medicine</a> as well as <a href="https://journals.lww.com/ajsp/Fulltext/2018/12000/Impact_of_Deep_Learning_Assistance_on_the.7.aspx">The American Journal of Surgical Pathology</a>, we showed how a proof-of-concept assistance tool (LYNA) could use deep learning to increase the accuracy of metastatic breast cancer detection. <a href="https://ai.googleblog.com/2018/10/applying-deep-learning-to-metastatic.html">Read the post</a></p> </div> </p> </div> </div> </div> </div> </div> </div> </div> </div> </div> <section class="g-h-block-style glue-mod-spacer-0-bottom"> <div class="glue-page g-h-health__wrapper g-h-imaging-diagnostics__content-section eye-disease-section"> <div class="g-h-text-slider-headline g-h-text-slider-4-headline glue-mod-text-center glue-grid__col--span-12"> <h2 class="glue-headline glue-headline--headline-3 glue-mod-spacer-4-bottom"> Detecting signs of disease from external images of the eye</h2> </div> <div class="g-h-content-block g-h-content-block--text-slider"> <div class="glue-grid content-block-grid"> <div class="glue-grid__col glue-grid__col--span-12-md glue-grid__col--align-middle glue-grid__col--span-6 glue-mod-order-1 glue-mod-order-2-md glue-mod-order-2-lg glue-mod-order-2-xl"> <div class="g-h-content-block__asset g-h-content-block__asset--reverse"> <div class="g-h-html-video"> <video id="video-mp4" class="g-h-html-video__player" autoplay muted playsinline loop> <source src="https://kstatic.googleusercontent.com/files/1a1760c60140a432faf9d577ce3d04c6acf30781b24b0148860f3feff073d2623da0552436ccabc065fa451e3d304a0174ca2c81d29447c433d74c259e5d2a9f" type="video/mp4"> </video> </div> </div> </div> <div class="g-h__desc-section glue-grid__col glue-grid__col--align-middle glue-grid__col--span-6 glue-grid__col--span-12-md glue-mod-order-2 glue-mod-order-1-md glue-mod-order-1-lg glue-mod-order-1-xl"> <div class="g-h-content-block__title glue-mod-spacer-3-bottom"> <h2 class="glue-headline glue-headline--headline-3">Exploring how external eye photos can reduce the need for specialised equipment</h2> </div> <div class="g-h-content-block__text"> <p>We’re doing research and building AI models that can not only decipher important information from retinal images, but also from external eye images. In our <a href="https://www.thelancet.com/journals/landig/article/PIIS2589-7500(23)00022-5/fulltext">research published in The Lancet Digital Health</a>, we have shown that a deep learning model can predict the presence of diabetic retinal disease and other biomarkers such as HbA1c or eGFR from external eye images alone. This could reduce the need for specialised equipment and expand access to care for the growing population of patients with diabetes or other chronic diseases. <a href="https://ai.googleblog.com/2023/03/detecting-novel-systemic-biomarkers-in.html">Read the post</a></p> </div> </div> </div> </div> </div> </section> <div class="glue-page g-h-health__wrapper"> <div class="glue-grid"> <div class="g-h-text-slider-headline glue-mod-text-center glue-grid__col--span-12"> <h2 class="glue-headline glue-headline--headline-3 glue-mod-spacer-3-bottom">Further research in imaging and diagnostics</h2> </div> <div class="g-h-text-slider-headline glue-mod-text-center glue-grid__col--span-2"></div> <div class="g-h-text-slider-headline glue-mod-text-center glue-grid__col--span-8"> <p class="glue-body">We continue to advance AI-enabled imaging research in other domains, expanding this technology to facilitate transformative diagnostics.</p> </div> <div class="g-h-text-slider-headline glue-mod-text-center glue-grid__col--span-2"></div> <div class="glue-grid__col glue-grid__col--span-12-md glue-grid__col--align-middle glue-grid__col--span-5 full-width-tab glue-mod-order-1-lg glue-mod-order-3-sm g-h-health_tab-align"> <div class="g-h-health-tabpanels glue-page"> <div class="glue-tabpanels glue-tabpanels--centeredtabs g-health-tabpanels-responsive" data-glue-tabpanels="tabs-noicons"> <div class="glue-tabpanels__page-list"> <div><p class="g-h-health-tab-title">AI Advances</p></div> <div><p class="g-h-health-tab-title">AI Learning</p></div> <div><p class="g-h-health-tab-title">AI Diagnosis</p></div> </div> <div class="glue-tabpanels__panel-list" data-glue-expansion-panels-key="imaging-panel-four"> <div id="tab-item-1-imaging-panel-four"> <div class="glue-tabpanels__panel-title"> <h2> AI Advances </h2> <svg role="presentation" aria-hidden="true" class="glue-icon glue-expansion-panel__button-arrow"> <use xlink:href="/static/img/glue-icons.svg#expand-more"></use> </svg> </div> <div id="tab-item-1-imaging-panel-four-content" class="glue-tabpanels__panel-content"> <div> <h3 class="glue-headline glue-headline--headline-4 glue-mod-spacer-2-bottom">Exploring AI advancements in radiotherapy planning to improve efficiency</h3> <p><div class="g-h-markdown glue-body"> <p>Building from work done with the University College London Hospitals and published in <a href="https://www.jmir.org/2021/7/e26151" rel="noreferrer noopener" target="_blank">JMIR Publications</a>, we are collaborating with Mayo Clinic to study the use of AI to help clinicians plan radiotherapy treatment for cancer. We’ve joined forces to research, train and validate an algorithm to assist physicians with segmenting healthy tissue and organs from tumours to reduce treatment planning time and improve the efficiency of radiotherapy, hopefully allowing clinicians to spend less time planning and more time with their patients. <a href="https://blog.google/technology/health/exploring-ai-radiotherapy-planning-mayo-clinic/">Read the post</a></p> </div> </p> </div> </div> </div> <div id="tab-item-2-imaging-panel-four"> <div class="glue-tabpanels__panel-title"> <h2> AI Learning </h2> <svg role="presentation" aria-hidden="true" class="glue-icon glue-expansion-panel__button-arrow"> <use xlink:href="/static/img/glue-icons.svg#expand-more"></use> </svg> </div> <div id="tab-item-2-imaging-panel-four-content" class="glue-tabpanels__panel-content"> <div> <h3 class="glue-headline glue-headline--headline-4 glue-mod-spacer-2-bottom">Using machine learning to detect deficient coverage in colonoscopy screenings</h3> <p><div class="g-h-markdown glue-body"> <p>Colorectal cancer (CRC) is a global health problem and the second deadliest cancer in the United States, resulting in an estimated 900,000 deaths per year. By alerting physicians to missed regions of the colon wall, our algorithm has the potential to lead to the discovery of more adenomas, thereby increasing the adenoma detection rate and decreasing the rate of interval colorectal cancer, as published in <a href="https://ieeexplore.ieee.org/abstract/document/9097918">IEEE Transactions on Medical Imaging</a>. <a href="https://ai.googleblog.com/2020/08/using-machine-learning-to-detect.html">Read the post</a></p> </div> </p> </div> </div> </div> <div id="tab-item-3-imaging-panel-four"> <div class="glue-tabpanels__panel-title"> <h2> AI Diagnosis </h2> <svg role="presentation" aria-hidden="true" class="glue-icon glue-expansion-panel__button-arrow"> <use xlink:href="/static/img/glue-icons.svg#expand-more"></use> </svg> </div> <div id="tab-item-3-imaging-panel-four-content" class="glue-tabpanels__panel-content"> <div> <h3 class="glue-headline glue-headline--headline-4 glue-mod-spacer-2-bottom">Using AI to identify the aggressiveness of prostate cancer</h3> <p><div class="g-h-markdown glue-body"> <p>To diagnose the severity of prostate cancer, biopsies are analysed and given a Gleason grade, which is scored on comparisons to healthy cells. In work published in <a href="https://jamanetwork.com/journals/jamaoncology/fullarticle/10.1001/jamaoncol.2020.2485">JAMA Oncology</a> and <a href="https://jamanetwork.com/journals/jamanetworkopen/fullarticle/2772831">JAMA Network Open</a>, we explored whether an AI system could accurately Gleason grade prostate biopsies, and our results indicated that the deep learning system has the potential to support expert-level diagnoses. <a href="https://blog.google/technology/health/using-ai-identify-aggressiveness-prostate-cancer/">Read the post</a></p> </div> </p> </div> </div> </div> </div> </div> </div> </div> <div class="glue-grid__col glue-grid__col--span-12-md glue-grid__col--align-middle glue-grid__col--span-1 glue-mod-order-2-lg glue-mod-order-2-sm"></div> <div class="glue-grid__col glue-grid__col--span-12-md glue-grid__col--align-middle glue-grid__col--span-6 full-width-tab glue-mod-order-3-lg glue-mod-order-1-sm"> <div class="g-h-html-video glue-mod-spacer-8-top"> <video 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