AI and Digital Health Innovation

• • Join MIDAS for the AI in Research Symposium 2026, a two-day event focused on how researchers are putting AI into practice. Through inspiring keynotes, hands-on research stories, and cross-campus connections, the symposium highlights how researchers are actually adopting AI and what it takes to move from curiosity to implementation. Whether you are just beginning to explore AI or already integrating it into your work, this event offers practical insights, candid lessons learned, and new ideas to take back to your research.

    • 🗓️ March 30–31, 2026 | 8:30 a.m. - 5:30 p.m.

    • 📍 Rackham Building | 915 E. Washington St. | Ann Arbor, MI 48109-1070

    • ✅ Register today! 

• Propelling Original Data Science (PODS) program (PODS) program 

  • In 2026, this program will use a more focused and strategic model to align with the evolving role of data science and AI in research. When the program was launched, its primary goal was to encourage adoption of emerging research methodologies. Today, AI and data science are being broadly integrated across disciplines, and the opportunity is no longer simple adoption but deeper transformation. This year’s PODS program is intentionally structured to support projects that strengthen research methodology, enable robust and reproducible data- and AI-enabled workflows, expand the frontier of research, and position U-M to lead in emerging areas. Through this revised framework, PODS aims to support projects that not only generate strong scholarship, but also build lasting institutional capacity and strategic advantage for the university. 

  • April 3, 2026: Letters of intent due

  • May 15, 2026: Full Proposals due

• GOOGLE.ORG IMPACT CHALLENGE: AI FOR SCIENCE. Accelerating scientific breakthroughs with the power of AI

  • Google.org is launching a supercharged initiative at the intersection of artificial intelligence and scientific discovery. By empowering researchers with catalytic funding and technical expertise, we aim to accelerate our understanding of key scientific questions—achieving Nobel-level breakthroughs and enabling science at digital speed.

  • The Google.org Impact Challenge: AI for Science is a $30M global open-call designed to empower researchers and organizations with the funding, tools, and technical expertise they need to accelerate scientific breakthroughs. Beyond funding, organizations may participate in a Google.org Accelerator and receive six months of dedicated pro bono technical support from Google experts and access to Google Cloud credits to help bring these projects to life.

  • Accepting applications until April 17, 2026 at 11:59PM PT.  

"How I Use AI" with Drs. Cornelius James and Hamid Ghanbari

Watch here

The inaugural FCVC Innovation “How I AI” session explores practical, thoughtful, and ethical ways to integrate generative AI into medical education, emphasizing critical engagement, tailored prompt engineering, and collaborative workflows—with plans to expand through more focused discussions and sharing best practices across the U-M network.

The following topics are discussed:

• philosophical concerns about AI in medicine

• principles and practices for using AI

• prompt engineering

• practical demonstration of using AI when preparing for a procedure or teaching, uploading relevant clinical papers, and receiving tailored outputs

• cross-model collaboration: using multiple AI models (e.g., ChatGPT, Gemini, Perplexity, Open Evidence)

"How I Use AI" with Drs. Sarah Adie and Hamid Ghanbari

Watch here

Dr. Ghanbari demonstrates various AI tools for academic research and learning, focusing primarily on Notebook LM, Google Gemini, and Claude. He shows how to use Notebook LM to read and analyze research papers more effectively, with features such as audio summaries, mind mapping, and interactive infographics. Dr. Ghanbari also shared his prompt framework for achieving better results with AI models and demonstrated an interactive tool he created with Claude to explain performance metrics. The discussion highlights how these tools can enhance research comprehension and teaching, specifically in medical education. 

"How I Use AI" with Drs. Tina Lasisi, Alberto Figueroa, and Hamid Ghanbari

Watch here

Dr. Lasisi shares her experience with both opportunities and challenges that AI tools offer in education. Drs. Lasisi and Ghanbari share their perspectives and address practical considerations for educators at the University of Michigan to integrate AI tools responsibly. 

Check out the U-M Center for Academic Innovation's AI-Powered Data Analysis: A Practical Introduction, instructed by Dr. Tina Lasisi.

• AI Institutes at Michigan (AIIM)

  • AIIM is designed to harness and enhance U-M’s existing capacities, aligning with our powerful public mission and Vision 2034. The establishment of AIIM is a proactive and necessary move, serving as a centralized declaration of U-M’s commitment to artificial intelligence and its continued development.

• 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.

  • AI Resources for Research at the University of Michigan *NEW FROM MIDAS*

• 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.

• 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.

• 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.

• 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.

• 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.

• 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

• How U-M researchers are tackling Artificial Intelligence to help transform healthcare (article)

• 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

• 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. 

• U-M Center for Academic Innovation's AI-Powered Data Analysis: A Practical Introduction instructed by Dr. Tina Lasisi

• Generative AI Workshop Series from ITS

• Visualization Tools for Researchers from the Office of Research Development (use umich.edu email to access)

• Picture Perfect: Designing Effective Graphics with Technology and AI session - Presentation from the Office of Research Development (use umich.edu email to access)

• 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

• Artificial Intelligence for Grant Writing

• University of Michigan Library Resource Guide for using AI 

• Wake Forest University's Speed Dating with AI tools video