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AI for Health is a philanthropic grant program from Microsoft Philanthropies that funds nonprofits, academic institutions, and researchers working on global health challenges through artificial intelligence technology and expertise. The program provides access to Azure cloud computing resources and collaboration with Microsoft's AI for Good Research Lab.
Funded projects focus on three main areas: integrating cross-sector health data for decision-maker insights, applying AI to clinical imaging to improve diagnostic precision and accessibility, and analyzing genomic and proteomic data to predict disease risks.
Since launching in January 2020, the program has partnered with more than 200 grantees, supporting research in cancer detection, smoking cessation, cardiovascular health, and global health equity. Nonprofits and academic researchers can apply through the Microsoft AI for Health program.
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AI for Health - Microsoft Research Human-computer interaction Human language technologies Data platforms and analytics Programming languages & software engineering Security, privacy & cryptography Medical, health & genomics Technology for emerging markets Events & academic conferences Microsoft Research podcast Microsoft Research newsletter Mixed Reality & AI - Cambridge Mixed Reality & AI - Zurich Software development companies Research and collaborations contributing to the Microsoft AI for Health program 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: 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.
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. 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.
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.
Understanding health equity 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.
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. Chatbot app aims to combat smoking addiction 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.
“It was very hard to get Quitbot to understand what people meant when they asked a question, we’ve come a long way and learned a lot about how to use natural language processing to be able to do it.
” – Dr. Jonathan Bricker, Professor, Cancer Prevention Program, Public Health Sciences Division, Fred Hutch Cancer Center Improving cancer diagnosis with computer vision Critical early detection of pancreatic cancer with AI 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. AI can help radiologists better detect breast cancer 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. Revolutionizing precision of prostate cancer diagnosis 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. “The 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.
” – Dr. Elliot K. Fishman, Professor of Radiology and Radiological Science The Microsoft AI for Health program: Solving the world’s biggest health issues, one life at a time William B. Weeks, Director of AI for Health in the AI for Good Research Lab, shares insights on the Microsoft AI for Health program.
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Based on current listing details, eligibility includes: Nonprofits, academic institutions, and researchers working on global health challenges. Applicants should confirm final requirements in the official notice before submission.
Current published award information indicates Varies (Azure cloud credits and AI for Good Lab collaboration) Always verify allowable costs, matching requirements, and funding caps directly in the sponsor documentation.
The current target date is rolling deadlines or periodic funding windows. Build your timeline backwards from this date to cover registrations, approvals, attachments, and final submission checks.
Federal grant success rates typically range from 10-30%, varying by agency and program. Build a strong proposal with clear objectives, measurable outcomes, and a well-justified budget to improve your chances.
Requirements vary by sponsor, but typically include a project narrative, budget justification, organizational capability statement, and key personnel CVs. Check the official notice for the complete list of required attachments.
Yes — AI tools like Granted can help research funders, draft proposal sections, and check compliance. However, always review and customize AI-generated content to reflect your organization's unique strengths and the specific requirements of the solicitation.
Review timelines vary by funder. Federal agencies typically take 3-6 months from submission to award notification. Foundation grants may be faster, often 1-3 months. Check the program's timeline in the official solicitation for specific dates.
Many federal programs offer multi-year funding or allow competitive renewals. Check the official solicitation for continuation and renewal policies. Non-competing continuation applications are common for multi-year awards.