AI Results

Can AI help predict outcomes in ovarian cancer?

International team of researchers awarded multimillion-dollar grant to apply AI to identify factors tied to long term survival

Epidemiology professor Leigh Pearce is leading an international team conducting AI-driven analysis to predict ovarian cancer survival and treatment response. Their analysis will help guide treatment selection and clinical trial recommendations.

AI grant targets deadliest form of ovarian cancer

University of Michigan researcher receives a multimillion-dollar grant to use AI to better predict survival and treatment outcomes for the most common and deadly form of ovarian cancer.

AI tool can predict heart failure from genetic and health record data

A University of Michigan study demonstrates that combining genetic and clinical data for an individual patient can help predict heart failure, the world’s leading cause of hospitalization, a decade before it’s diagnosed.

On the Heights: May 2025

Departmental news, research highlights, community achievements, and more to help you stay connected with the Michigan Public Health community.

Biostatisticians use machine learning approach to improve risk prediction for recurrent health events

"Random forest" algorithm outperforms traditional methods for predicting patient flare-ups, even with incomplete medical histories

A new machine learning approach developed by University of Michigan School of Public Health researchers better predicts when patients might experience recurring health events like disease flare-ups or hospitalizations, even when patient follow-up data is incomplete.

U-M Precision Health joins with Michigan Genomics Initiative and e-Health & AI to become AI & Digital Health Innovation

The AI and Digital Health Innovation collective combines the focused efforts of two core communities representing the diverse, high-impact areas of digital health research taking place across U-M.