The AI for Health Institute (AIHealth) brings together AI researchers and health investigators to forge new paths to solve significant health problems with advanced AI technologies.

Call for Proposals

We are launching the AI for Health Seed Funding program in partnership with the Here and Next Seed Grant initiative. The application portal is now open, with a submission deadline of March 1, 2025.

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Researchers define new subtypes of common brain disorder

Researchers define new subtypes of common brain disorder

Artificial intelligence identified 3 subtypes of Chiari type-1 malformations, could improve medical decision making

AI for Health Symposium

AI for Health Symposium

AIHealth hosted leading AI researchers and health experts to explore innovative, data-driven solutions to today’s most pressing healthcare and public health challenges.

AI for Health Seed Grant

AI for Health Seed Grant

We are launching the AI for Health Seed Funding program in partnership with the Here and Next Seed Grant initiative. The application portal is now open, with a submission deadline of March 1, 2025.

School of Medicine joins AI collaborative 

School of Medicine joins AI collaborative 

Drs. Payne and Maddox named corps site leads

Deep learning models can be trained with limited data

Deep learning models can be trained with limited data

Ulugbek Kamilov, graduate students, develop method that could reduce errors in computational imaging

DEMIST artificial intelligence tool may enhance usability of medical images

DEMIST artificial intelligence tool may enhance usability of medical images

A deep-learning-based image denoising method developed by Abhinav Jha may improve detection of myocardial defects in low-count SPECT scans

What Your Fitness Tracker Says About Your Mental Health

What Your Fitness Tracker Says About Your Mental Health

Chenyang Lu delves into innovative research utilizing AI and wearable technology to detect depression and anxiety disorders.

New machine learning method can better predict spine surgery outcomes

New machine learning method can better predict spine surgery outcomes

Researchers at Washington University in St. Louis combine artificial intelligence and mobile health data to better predict recovery from lumbar spine surgery.

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