AI and Digital Health Innovation

Johnson & Johnson MedTech Polyphonic™ AI Fund for Surgery QuickFire Challenge

Researchers and innovators in the Surgical Data Science field worldwide are invited to submit ideas for AI technologies that have the potential to improve surgical decision-making, strengthen data management & governance processes, and drive surgical efficiency across the connected operating room (OR). LOI Deadline: August 1, 2025

• 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.

• 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. 

• Michigan Integrated Center for Health Analytics & Medical Prediction (MIChamp)

  • Through population-based approaches that leverage “Big Data” tools, this work seeks to improve the delivery and quality of specialized healthcare services.

• 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

• University of Michigan Artificial Intelligence Laboratory

  • A research group that includes faculty, research scientists, graduate students, and postdoctoral fellows working in AI.

• 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. 

• Applying Natural Language Processing to Improve Patient Care - MICHR Video

• GenAI Training for Administrators

• FDA Digital Health and Artificial Intelligence Glossary

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