Duke AI Health hosted two virtual seminars designed to support the Duke research community as it transitions from PACE to the Protected Research Compute Cluster (PRCC). The first session, PACE to PRCC: Introduction for School of Medicine Researchers, provided an overview of the PRCC’s architecture and expanded capacity. The second session, PACE to PRCC: Managing Your Project Transition, guided users through what to expect as projects begin moving into the new environment. These virtual seminars were led by a multidisciplinary team of experts from Biostatistics and Bioinformatics, Duke Health Technology Solutions (DHTS) and the School of Medicine, including Ricardo Henao, Jay Stotler, Aby Veiga, Danny Williford, John Bradley, and were hosted by AI Health Managing Director, Shelley Rusincovitch. The recorded content, slides and links are available to the Duke community on the Data Science SharePoint.

LINKS

• The Protected Research Compute Cluster: Introduction for School of Medicine Researchers
• PACE to PRCC: Managing Your Project Transition

Benjamin Goldstein, PhD, Duke AI Health’s Director of Data Science, was among the participants at the Department of Medicine’s second Artificial Intelligence and Medicine Symposium on February 3. The event, which revolved around the theme of AI’s transformative impact on medicine and research, included individual presentations and panel discussions, was capped by a resource fair. Dr. Goldstein took part in a panel focused on AI-centered collaborations in health research that was moderated by Vice Dean for Data Science & AI Christopher Lindsell, PhD.

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A new case study led by students and faculty from Columbia University and Duke, including Duke School of Nursing professor and AI Health Faculty Council member Michael Cary, PhD, and doctoral student Thomas Merrill explores how nurses increasingly encounter patients who bring AI-generated health information to the bedside. The paper highlights the ethical and clinical tensions that arise when AI tools interpret medical data without clinical context, and it introduces practical communication strategies nurses can use to navigate these situations. The authors propose two structured approaches—Ask-Balance-Clarify-Document for communication with patients and AI-SBAR for communication with clinical teams —to help nurses address AI-generated information safely and ethically.

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AI Health faculty affiliate Chuan Hong, PhD, whose American Heart Association–supported research evaluates the PREVENT equations for 10-year atherosclerotic cardiovascular disease risk, mentored graduate student Ziye Tian. Tian received a Travel Award for Junior Investigators to present her work, “Toward a Deeper Understanding of PREVENT for 10 Year Atherosclerotic Cardiovascular Risk: Subgroup Fairness and Predictive Value of Social Determinants of Health,” at the International Stroke Conference 2026. In extensive analyses using data from Truveta electronic health records, Tian assessed model fairness across demographic and social determinants of health subgroups and examined the added predictive value of those social determinants of health.

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Duke AI Health Research Scientist Whitney Welsh, PhD, presented a poster, “The Duke AI Health Community of Practice: A Model for Increasing AI Proficiency and Critical Understanding,” at the Conference on Society-Centered AI in Durham this February. Welsh and co-author Shelley Rusincovitch, MMCi, AI Health managing director, described the process of creating a logic model for the Duke AI Health Community of Practice and shared results from last year’s feedback survey, which show that the Community of Practice is achieving many of its short-term goals.

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This article was originally published by the Duke Pratt School of Engineering. You can learn more about Dr. Dunn and his work with the DANNCE 3D mapping program, which was supported by Duke Forge, a precursor organization to AI Health, in an article available at the Duke AI Health website.

The subjects in the research videos created by Timothy Dunn, an assistant professor of biomedical engineering at Duke University, aren’t immediately obvious. Rather than show tufts of fur or swishing tails, the animal models––usually mice or rats––are instead depicted by straight lines and colorful dots that move around an otherwise empty screen.

These videos are created through the program DANNCE, short for 3-Dimensional Aligned Neural Network for Computational Ethology, a tool Dunn and his team developed in 2021. Using videos of freely moving rats, the team trained machine-learning algorithms and neural networks to identify and map the precise 3D locations of the body joints on the animals. Researchers could then relate these measurements to data collected from brain recording technologies to examine links between neuronal activity and specific behaviors.

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This past December’s Data Science Poster Showcase, co-hosted by Duke AI Health, Duke Pratt School of Engineering, the Duke Center for Computational Thinking, the Duke Center for Computational and Digital Health Innovation, and Duke Health, included a “People’s Choice” award for best poster presentation. For this category, showcase attendees were able to cast votes for their favorite entries. The Vox Populi Award for 2025 was a tie, with awards going to Logan Bailey and Charles Scales for “Enhancing Translation Efficiency: Evaluating AI Assisted Translation for Clinical and Research Documents,” and to Jaden Sacks and colleagues for “Beyond Advance Directives: A Machine Learning Tool to Aid End-of-Life Decisions in Dementia Care.”

Please join us in congratulating our winners!

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This March, the Duke AI Health Community of Practice hosted the Machine Learning School: Health AI (MLSS-HealthAI), the 13th in the ML School Series since 2017. Machine learning expert Ricardo Henao, PhD, led the three-day program, which featured 10 expert presenters from across Duke. The event brought together 149 participants representing 58 organizations, including 56 students and 22 scholarship recipients (in keeping with its educational mission, the Community of Practice reserved a minimum of 10% of seats for scholarships to support attendance by those who would otherwise be unable to attend).

A major highlight of this year’s event was the hands-on use of the Duke Health AI Studio, which offers a variety of AI platforms for Duke users in a protected environment. With help and expert guidance from Duke Health Technology Solutions (DHTS), participants were able to explore real-world examples, and apply new techniques in an immersive computing environment.

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In February, a select steering committee representing multiple schools, institutes and disciplines across Duke University published a report on artificial intelligence to the Duke University Provost. The report synthesized perspectives on Duke’s strengths in AI as well as gaps and opportunities, including the potential for improving institutional approaches to developing, applying, and providing ethical oversight for these technologies at the university. The Steering Committee, whose leadership included Duke AI Health Faculty Council Member Ricardo Henao, PhD, as a co-chair, also examined infrastructural needs for AI at Duke and articulated a strategic vision for the future of human-centered AI in research and education.

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On March 29, Duke University Executive Vice President for Health Affairs and School of Medicine Dean Mary E. Klotman, MD, announced that Duke Clinical Research Institute Director of Data Science Christopher Lindsell, PhD, has been appointed to serve as Vice Dean for Data Science & AI at the Duke University School of Medicine, effective April 1. In this new role, Dr. Lindsell will lead the strategy, execution, and governance of AI and data science across the School of Medicine while collaborating closely with key partners in the Duke University Health System and the university. His immediate priorities include advancing a unified strategy for AI research, education, and workforce training, as well as building multidisciplinary teams, coordinating platform development and oversight, and accelerating our learning health system to ensure that discovery, clinical decision‑making, and operations at Duke are informed by the highest-quality data possible. READ MORE