Pencina

AI Health Director Pencina Interviewed for Article on Medical AI Hallucination

“’The question is, again, what are the consequences of it?’ The answer, to him, rests in the stakes of making an error – and with healthcare, those stakes are serious.” The Verge’s Hayden Field interviews AI Health Director Michael Pencina, PhD, for an article that probes the implications of recent reports suggesting that a specialized medical large language model chatbot – Google’s Med-Gemini – may have hallucinated a nonexistent anatomical feature. The lapse, which made its way unrecognized into a preprint paper posted by Google, has raised concerns among AI researchers.

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Duke Authors Examine Limitations of Binary Classification for Diagnosis Prediction

A group of authors from Duke, including AI Health Data Science Fellow Elliot Hill and Data Science Fellowship Director Matthew Engelhard, published a research article that examined the propensity for a supervised machine learning approach known as binary classification to yield biased results when predicting long-horizon diagnoses. The paper, titled “Limitations of Binary Classification for Long-Horizon Diagnosis Prediction and Advantages of a Discrete-Time Time-to-Event Approach: Empirical Analysis,” was published in March in the journal JMIR AI.
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AI Health Seminar Series Rewind: Real-World Applications of AI Chatbots with ChatGPT

Duke Office of Information Technology Media Architect and Senior Producer Stephen Toback explores the capabilities and limitations of AI chatbots like ChatGPT in healthcare and academia. The session demonstrates real-world use cases ranging from clinical documentation to administrative support. Toback also addresses common pitfalls, such as hallucinations and privacy concerns, providing guidance on safe implementation. It’s a practical guide for institutions considering integrating generative AI tools. 

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Dr. Michael Cary Speaks at Congressional Briefing on Impact of Nursing Science on Patient Care

Dr. Michael Cary, Duke AI Health faculty council member and Associate Professor and Elizabeth C. Clipp Term Chair of Nursing in the Duke University School of Nursing, was invited to speak at a congressional briefing titled Powered by Evidence: Quality Patient Care Requires Nursing Science. Hosted by the American Academy of Nursing (AAN) and the American Association of Colleges of Nursing (AACN), the event took place in Washington, DC and spotlighted the critical role of nursing science in improving patient care. Dr. Cary joined a distinguished panel that included nurse scientist Jeanne Alhusen, patient advocate Johane Joseph, and moderator Antonia Villarruel, Dean of the University of Pennsylvania School of Nursing. This national platform highlights Duke’s leadership in nursing research and health equity.

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AURORA Study Sifts Electronic Records for Clues to Better Understand Autism in Children

Researchers working with the Duke Center for Autism and Brain Development are conducting an innovative study that seeks to harness machine learning techniques to spot potential signs of autism in the electronic health data of young children.

“Duke data scientists, autism researchers, and healthcare professionals are collaborating to help pediatric providers optimize care for children with neurodevelopmental differences. By leveraging routinely collected health data, they aim to address a critical need for efficient, consistent, and objective methods for early autism screening.”

“’We know from previous work in the ACE [Autism Center of Excellence] that certain early childhood medical conditions can be indicative of a future autism diagnosis,’ said Benjamin Goldstein, PhD, director of data science at Duke AI Health and lead investigator on the study.”

–Story by Evan Watson, MLS

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Call for Applications: Fall 2025 Medical Imaging & AI Health Proposal Studios

Duke Spark, with support from Duke AI Health, invites faculty across Duke to apply for the Fall 2025 Medical Imaging and AI Proposal Studios, a unique opportunity to receive expert feedback and mentorship on grant proposals at the intersection of AI, computer vision, and medical imaging. Designed to support high-impact and competitive research, this initiative is open to clinical and non-clinical faculty from all Duke departments, with special encouragement for early-career investigators. Selected projects will participate in tailored scientific review sessions held from October to December 2025. Applications are due by 10:00 PM ET on Monday, September 8, 2025.

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Registration Open for Duke Summit on AI for Health Innovation: October 8-9, 2025!

Duke AI Health, the Duke Clinical Research Institute, and the Duke Center for Computational and Digital Health Innovation are thrilled to announce the second annual Duke Summit on AI for Health Innovation, that will take place October 8-9, 2025. This event aims to foster a vibrant community of practice that bridges the medical and engineering fields to advance health-oriented AI development. The summit will spotlight Duke’s expertise in AI product development and healthcare innovation, emphasizing the use of responsible AI to improve health outcomes for patients and communities. Please join us in shaping the future of AI for health!

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AI Health Spark Seminar Series: Neuroimage Analysis in Autism: From Model-Based Estimation to Data-Driven Learning

This seminar, presented by James S. Duncan, PhD, and hosted by Maciej Mazurowski, PhD, explores advanced neuroimaging analysis in autism spectrum disorders (ASD), with a focus on identifying objective biomarkers and predicting response to behavioral therapies such as Pivotal Response Treatment (PRT). Dr. Duncan presents a range of methodologies, beginning with a Bayesian framework to detect atypical brain connectivity and moving toward machine learning approaches that use convolutional and recurrent neural networks for classification and prediction. The talk also discusses early work involving dynamic causal modeling as a complementary approach to traditional functional connectivity methods. These techniques offer promising tools for individualized diagnosis, treatment planning, and monitoring in ASD. This seminar originally aired on March 7th, 2023. This session was part of the monthly Spark: AI Health Initiative for Medical Imaging seminar series. Spark highlights cutting-edge work in medical imaging research from Duke and beyond, with a mission to develop, validate, and implement AI tools for clinical imaging. The series fostered collaboration between technical and clinical experts. VIEW

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Duke AI Health Authors Present Delphi Framework for Heath AI

Duke AI Health Research Scientist Whitney Welsh, PhD and Managing Director Shelley Rusincovitch, MMCi, FAMIA, have published an abstract describing the use of a Delphi framework for developing effective educational strategies to address unmet needs in the domain of health AI. The abstract, titled “Using the Delphi Method to Strategize About Health AI,” was published in a supplemental issue of the Journal of Clinical and Translational Science after having been presented as a poster by Dr. Welsh at the annual meeting of the Association for Clinical and Translational Science in Washington, D.C. in April of 2025.

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