AI and Digital Health Innovation

How U-M researchers are tackling Artificial Intelligence to help transform healthcare

University of Michigan Remote and Mobile Tech Expertise Finder

• A tool to help researchers and their teams identify other U-M faculty and staff with experience in specific remote and mobile technologies

U-M AI and Digital Health Innovation

• Supports team science approaches to solving complex AI and digital health problems.

• AI & Digital Health Innovation, formerly Precision Health, was launched as a Presidential Initiative in 2017. AI & Digital Health Innovation now represents a unification and enhancement of interdisciplinary efforts at the intersection of artificial intelligence (AI) and health at the University of Michigan.

• AI & Digital Health Innovation provides research implementation support to strategically integrate and study AI models in clinical workflows at Michigan Medicine, in addition to a robust foundation in data services and secure computing resources. They also drive critical efforts focused on health at U-M and contribute to the upcoming transformative initiatives that will place U-M as “Leaders & Best” in AI for health.

Data Augmented Technology Assisted Medical Decision Making Course (DATA-MD)

• DATA-MD is a one-of-a-kind curriculum designed to provide an introduction to the use of AI in the diagnostic process.

E-health and Artificial Intelligence (eHAIL)

• e-HAIL is a joint Michigan Medicine and College of Engineering initiative that aims to make U-M a premier hub for research that innovates in health through AI.

Michigan Institute for Data and AI in Society (MIDAS)

• University of Michigan organization that advances data science and artificial intelligence (AI) and enables their transformative use across a wide range of research domains for lasting scientific and societal impact.

Surgical Practice AI Community (SPARC)

• The Surgical Practice AI Research Community (SPARC) is a multi-institutional community connecting surgeons, computer scientists, informaticists, ethicists, health services researchers, implementation scientists, and any other stakeholders involved in the application of artificial intelligence (AI) in healthcare. Our aim is to foster a welcoming community dedicated to ensuring AI is implemented in healthcare safely, efficiently and sustainably to benefit providers and patients.

DIGIT-MI (Eisenberg Depression Center)

• DIGIT-MI is an affinity group where University of Michigan faculty and staff meet to connect, learn, and share resources that encourage using digital and mobile technologies and mental wellness measurements in health research. 

ITS Advanced Research Computing (ARC) 

• ARC provides support and referral for many kinds of research computing and many aspects of research computing, from programming to data storage services. 

ITS AI Service

• ITS is now offering a generative AI platform available to all active U-M faculty, staff, and students on the Ann Arbor, Flint, and Dearborn campuses and Michigan Medicine. These service offerings are equitable and accessible, and support everything from basic consumer usage to advanced research and experimentation.

University of Michigan Institute for Healthcare Policy and Innovation (IHPI) Artificial Intelligence Experts

Generative Artificial Intelligence Advisory (GAIA) Committee

• The GAIA Committee guides the University of Michigan community on the use of generative AI and provides strategic advice to the VPIT-CIO and Provost.

American Medical Association ChangeMedEd® Training Series

• This series, developed by the American Medical Association ChangeMedEd® initiative and the University of Michigan DATAMD team, introduces learners to foundational principles in artificial and augmented intelligence (AI) and machine learning (ML) through a series of seven online activities. The DATA-MD team includes U-M's Andrew Wong, M.D., and Cornelius James, M.D. 

Data and AI Intensive Research with Rigor and Reproducibility (DAIR³)

• The Data and AI Intensive Research with Rigor and Reproducibility (DAIR3) program includes weeklong bootcamps in the summer that focus on ethical issues in biomedical data science; data management, representation, and sharing; rigorous analytical design; the design and reporting of AI models; generative AI; reproducible workflow; and assessing findings across studies. Additionally, the bootcamp also includes grant writing sessions and research collaboration discussions

• Session #1: Monday, May 18 – Saturday, May 23, 2026 at University of Michigan – Ann Arbor, MI 

• Priority Application Deadline: Jan. 30, 2026

Applying Natural Language Processing to Improve Patient Care - MICHR Video

GenAI Training for Administrators

Elements of AI - Free Online Course

Coursera - AI for Everyone Course (Free)

FDA Digital Health and Artificial Intelligence Glossary

GenAI Micro-Learning courses (through U-M ITS)

ACC Article, October 2025 - Empowering the AI-Enabled Clinician