{"id":778522,"date":"2023-05-16T14:26:13","date_gmt":"2023-05-16T21:26:13","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/?post_type=msr-project&p=778522"},"modified":"2024-10-14T15:42:21","modified_gmt":"2024-10-14T22:42:21","slug":"ai-for-health","status":"publish","type":"msr-project","link":"https:\/\/www.microsoft.com\/en-us\/research\/project\/ai-for-health\/","title":{"rendered":"AI for Health"},"content":{"rendered":"
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AI for Health<\/h1>\n\n\n\n

Research and collaborations contributing to the Microsoft AI for Health program<\/p>\n\n\n\n

< AI For Good Lab<\/a><\/p>\n\n\t\t\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t<\/div>\n\t\t<\/div>\n\t<\/div>\n<\/section>\n\n\n\n\n\n

AI for Health is a philanthropic program launched by Microsoft, which aims to support nonprofits, researchers, and organizations working on global health challenges. The program provides access to artificial intelligence (AI) technology and expertise in three main areas:<\/p>\n\n\n\n

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Population health<\/strong><\/p>\n\n\n\n

By integrating data from various health sectors and utilizing AI and visualization techniques, the program aims to offer decision-makers valuable insights into the factors driving diseases.<\/p>\n<\/div>\n\n\n\n

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Imaging analytics<\/strong><\/p>\n\n\n\n

AI is applied to image-based data to improve clinical decision-making processes, extend the reach of imaging tools, and enhance their precision and accuracy.<\/p>\n<\/div>\n\n\n\n

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Genomics & proteomics<\/strong><\/p>\n\n\n\n

AI is utilized to analyze genomic and proteomic data. It can help predict disease risks and identify specific areas in proteins that require further investigation for potential disease intervention.<\/p>\n<\/div>\n<\/div>\n\n\n\n

Since its launch in January 2020, the AI for Health Program has partnered with more than 200 grantees, supporting projects that accelerate medical research, enhance research capabilities, increase global health insights, and address health inequities.<\/p>\n\n\n\n

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Protecting public health<\/h2>\n\n\n\n
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Understanding health equity<\/h4>\n\n\n\n

The AI for Health dashboard provides an opportunity for researchers and other interested parties to easily explore relationships between county-level measures of health status, health services utilization and quality, and social determinants of health.<\/p>\n\n\n\n

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AI4HealthyCities<\/h4>\n\n\n\n

AI4HealthyCities is an initiative by the Novartis Foundation in collaboration with Microsoft AI for Health and local partners, bringing together existent but disconnected sets of data within a city and using advanced analytics and AI to uncover cardiovascular risk factors in its population.<\/p>\n\n\n\n

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Chatbot app aims to combat smoking addiction<\/h4>\n\n\n\n

Over 1.3 billion individuals are regular smokers, causing 7.7 million annual deaths, with 1.3 million non-smokers affected by second-hand smoke exposure. To combat this epidemic, the AI for Good Lab worked together with Fred Hutch to develop a chatbot app for smoking cessation.<\/p>\n\n\n\n

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“It was very hard to get Quitbot to understand what people meant when they asked a question, we\u2019ve come a long way and learned a lot about how to use natural language processing to be able to do it.\u201d<\/p>\n\u2013 Dr. Jonathan Bricker, Professor, Cancer Prevention Program, Public Health Sciences Division, Fred Hutch Cancer Center<\/cite><\/blockquote>\n\n\n\n

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Improving cancer diagnosis with computer vision<\/h2>\n\n\n\n
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Critical early detection of pancreatic cancer with AI<\/h4>\n\n\n\n

85% of people with pancreatic cancer are diagnosed too late to receive life-saving treatment. Early diagnosis is crucial, yet in ~ 40% of CT scans, tumors are not detected. Working together with Fred Hutch we are training AI to identify tumors often missed by the human eye, potentially saving up to 30,000 lives annually.<\/p>\n\n\n\n

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AI can help radiologists better detect breast cancer<\/h4>\n\n\n\n

Breast cancer is the second leading cause of cancer related death in women, early detection is critical for improving treatment outcomes. Learn how AI is helping professionals quickly learn from thousands of patient images to improve the way we detect, diagnose, and rule out false positives.<\/p>\n\n\n\n

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Revolutionizing precision of prostate cancer diagnosis<\/h4>\n\n\n\n

Prostate cancer, the second most diagnosed cancer in men, claims over 350,000 lives yearly. Automated lesion segmentation in radiological PET CT scans promises personalized treatment and enhanced monitoring. While AI won’t replace radiologists, it enhances precision and efficiency.<\/p>\n\n\n\n

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\u201cThe truth is companies outside of medicine can really have the biggest impact. If medicine wants to move forward, they need to work closely with the best computer scientists because we understand the problem and they know how to find the solutions.\u201d<\/p>\n\u2013 Dr. Elliot K. Fishman, Professor of Radiology and Radiological Science<\/cite><\/blockquote>\t\t<\/div>\n\t<\/div>\n\n\t<\/div>\n\n\n\n

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The Microsoft AI for Health program: Solving the world\u2019s biggest health issues, one life at a time<\/h3>\n\n\n\n

William B. Weeks, Director of AI for Health in the AI for Good Research Lab, shares insights on the Microsoft AI for Health program.<\/p>\n\n\n\n

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Read the blog<\/a><\/div>\n<\/div>\n<\/div>
\"AI<\/figure><\/div>\n\n\n","protected":false},"excerpt":{"rendered":"

AI for Health is a philanthropic program launched by Microsoft, which aims to support nonprofits, researchers, and organizations working on global health challenges. The program provides access to artificial intelligence (AI) technology and expertise in three main areas: population health, imaging analytics, genomics & proteomics.<\/p>\n","protected":false},"featured_media":905565,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"_classifai_error":"","footnotes":""},"research-area":[13556,13553],"msr-locale":[268875],"msr-impact-theme":[261673],"msr-pillar":[],"class_list":["post-778522","msr-project","type-msr-project","status-publish","has-post-thumbnail","hentry","msr-research-area-artificial-intelligence","msr-research-area-medical-health-genomics","msr-locale-en_us","msr-archive-status-active"],"msr_project_start":"","related-publications":[1020165,1115808,1097580,1096548,1090515,1090473,1078143,1063071,1049124,1020291,1020282,1122408,1020123,1020117,1006449,998577,998547,998514,998508,984477,980718,1147627,1163426,1162996,1160022,1160020,1160016,1158576,1152512,1151364,1148874,967278,1147625,1144923,1141267,1138548,1138132,1133494,1133010,1131114,1124457,757426,833545,833533,821485,802924,801157,776404,776392,776380,759400,837133,757420,745216,727471,702154,697009,696970,696811,696775,696721,931305,967254,964680,958926,949449,939687,937545,937533,934299,933249,696577,931242,914718,909825,898092,897231,878778,871371,868782,854193],"related-downloads":[],"related-videos":[],"related-groups":[780706,916890],"related-events":[],"related-opportunities":[],"related-posts":[467505,692679,707932,1124682],"related-articles":[],"tab-content":[],"slides":[],"related-researchers":[{"type":"user_nicename","display_name":"Bill Weeks","user_id":39582,"people_section":"Section name 0","alias":"wiweeks"},{"type":"user_nicename","display_name":"Anthony Ortiz","user_id":39715,"people_section":"Section name 0","alias":"anort"},{"type":"user_nicename","display_name":"Caleb Robinson","user_id":39606,"people_section":"Section name 0","alias":"davrob"},{"type":"user_nicename","display_name":"Darren Tanner","user_id":41404,"people_section":"Section name 0","alias":"datanner"},{"type":"user_nicename","display_name":"Felipe Oviedo","user_id":39925,"people_section":"Section name 0","alias":"juoviedo"},{"type":"user_nicename","display_name":"Juan M. Lavista Ferres","user_id":39552,"people_section":"Section name 0","alias":"jlavista"},{"type":"user_nicename","display_name":"Meghana Kshirsagar","user_id":39736,"people_section":"Section name 0","alias":"mekshirs"},{"type":"user_nicename","display_name":"Rahul Dodhia","user_id":41401,"people_section":"Section name 0","alias":"radodhia"},{"type":"user_nicename","display_name":"Santiago Salcido","user_id":42255,"people_section":"Section name 0","alias":"ssalcido"},{"type":"user_nicename","display_name":"Shahrzad Gholami","user_id":39757,"people_section":"Section name 0","alias":"sgholami"},{"type":"user_nicename","display_name":"Yixi Xu","user_id":39775,"people_section":"Section name 0","alias":"yixx"}],"msr_research_lab":[],"msr_impact_theme":["Health"],"_links":{"self":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-project\/778522","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-project"}],"about":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/types\/msr-project"}],"version-history":[{"count":75,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-project\/778522\/revisions"}],"predecessor-version":[{"id":1093440,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-project\/778522\/revisions\/1093440"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/media\/905565"}],"wp:attachment":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/media?parent=778522"}],"wp:term":[{"taxonomy":"msr-research-area","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/research-area?post=778522"},{"taxonomy":"msr-locale","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-locale?post=778522"},{"taxonomy":"msr-impact-theme","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-impact-theme?post=778522"},{"taxonomy":"msr-pillar","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-pillar?post=778522"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}