Please help us make AI Health’s Community of Practice better! In this brief survey, we are trying to get a sense of what AI Health offerings you may have found useful or valuable over the past year. Have you participated in any of our classes or seminars? Have you attended one of our conferences or summits? Are you enjoying the Friday Roundup? Are there any ways we can improve or serve you better?

Take the survey here: https://duke.qualtrics.com/jfe/form/SV_3sCUufSFTxCiMsu

The responses from last year’s impact survey were extremely helpful in our planning for this year’s offerings.  We are genuinely interested in what you have to say, and what we can do to improve on what we are doing! Check out last year’s results at https://duke.is/2025-ai-health-survey-summary

The linked Qualtrics survey is anonymous and should only take a few minutes to complete. As an added incentive, participants who complete their surveys may choose to enter a raffle for Duke AI Health mugs and stickers.  We very much appreciate your feedback!

Duke AI Health Program Coordinator Tiffany Torres recently earned her SHRM-CP (Society for Human Resource Management–Certified Professional) credential. This nationally recognized certification reflects advanced expertise in people operations, workplace policies, and employee support—capabilities that strengthen internal team performance while enhancing collaboration with external partners and sponsors. Her accomplishment underscores a commitment to supporting effective, well-coordinated teams and the people-centered practices that enable Duke AI Health’s work at the intersection of AI and health. Please join us in congratulating Tiffany on this achievement!

A paper co-authored by Duke AI Health researchers Christine Shen, Christian Péan,MD, and Samuel Berchuck, PhD, received a Student Paper Award from the Bayesian Statistical Science Section of the American Statistical Association. The work introduces a new spatial modeling approach to identify geographic patterns in hospital readmission risk following upper extremity fracture surgery while accounting for competing mortality risk. Using high-resolution maps, the team highlights local areas where patients face elevated risk, creating opportunities for targeted, community-level interventions. This framework demonstrates how advanced statistical methods can translate complex health data into actionable insights for population health and care delivery.

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The Duke AI Health Community of Practice is pleased to host the Duke Machine Learning Spring School 2026: Health AI (MLSS-HealthAI), offered in March as an in-person three-day class that will provide perspective and insight on the fundamentals of generative artificial intelligence methods and applications. The curriculum in the MLSS-HealthAI is targeted to individuals interested in learning about generative AI with health applications and will introduce the mathematics and statistics at the foundation of current generative and representation learning models, plus provide context for the methods that have formed the foundations of rapid growth in AI. Additionally, the MLSS-HealthAI will provide hands-on experience during practical sessions that illustrate the use of such methods and applications. LEARN MORE

In June 2025, scientific collaborators from Duke AI Health and the American Heart Association, led by principal investigator and former AI Health Director Michael Pencina, PhD, concluded a five-year study funded by the National Institutes of Health and designed to improve the ability to predict a patient’s risk of stroke. After aggregating and harmonizing patient-level data collected from four NIH-sponsored observational cohort studies, the study investigators evaluated the performance of existing stroke risk prediction models, developed new models with the potential to improve clinical decision-making, and explored ways to mitigate algorithmic bias and improve the fairness of models in clinical use. Key findings from the study have been shared through 18 publications in high-impact academic journals and conference proceedings, and the code used to conduct analyses is publicly available through the study’s dedicated GitHub repository.

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This fall, the Duke AI Health Community of Practice successfully concluded its third Scientific Writing Workshop for Staff. This four-unit minicourse is designed to offer a wide-ranging introduction to scientific writing and peer-reviewed publication. AI Health Research Scientist Whitney Welsh, PhD, has created an impact report (linked below) that provides a detailed snapshot of how this most recent iteration of the program was received. In December, workshop participants presented the research posters they developed as a key class project at the 2025 Health Data Science Poster Showcase. Congratulations and thanks to all of our workshop participants for making the fall 2025 offering such a success!

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This December, Duke AI Health partnered with the Pratt School of Engineering, the Duke Center for Computational Thinking, the Duke Center for Computational and Digital Health Innovation, and Duke Health to present the fourth Data Science Poster Showcase. The Showcase is a recurring semiannual event designed to provide a forum that allows Duke staff, students, trainees, and faculty to highlight their work, research, or class projects, while also gaining experience in presenting their projects to a larger audience. This year’s event encompassed over 60 posters on topics that included statistics, biomedical informatics, epidemiology, machine learning, implementation science, process engineering, quality improvement, among many others.

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Earlier this month, Duke University Executive Vice President for Health Affairs and School of Medicine Dean Mary Klotman, MD, announced the launch of Discovery AI, a new strategic research initiative designed to accelerate the application of artificial intelligence and machine learning to discovery science in biomedicine. Discovery AI is focused on deeply integrating computational and biological expertise with the goal of extending the frontiers of biological discovery across multiple scales. Scott H. Soderling, PhD, chair of the Department of Cell Biology, interim chair of the Department of Biochemistry, and David Page, PhD, chair of the Department of Biostatistics and Bioinformatics, will lead an effort that combines excellence in biology, engineering, and data science in a seamless and collaborative framework, bringing quantitative and experimental approaches into closer alignment. Duke AI Health Faculty Council member Ricardo Henao, PhD, is among numerous faculty experts who will be contributing to the initiative.

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Our 2025 Duke AI Health Friday Roundup series continued to offer a weekly collection of notable news and views on AI, clinical research, basic science, and more, drawn from the scholarly literature, tech reporting, and broader media.

In December, Duke AI Health’s Community of Practice, in partnership with the Duke Pratt School of Engineering, the Duke Center for Computational and Digital Health Innovation, and Duke Health, hosted the 2025 Health Data Science Poster Showcase. The event, which was open to Duke students, trainees, staff, and faculty, also included participants in the Fall 2025 AI Health Foundations of Scientific Writing for Staff Workshop.