Duke University School of Medicine is home to multiple initiatives and centers aimed at advancing the frontiers of artificial intelligence and machine learning in medicine and healthcare. The School encompasses a broad array of multidisciplinary collaborations in AI for healthcare focused on discovery science, clinical research, patient care, community engagement, governance, and education and training.

Duke AI Health

Duke AI Health’s core mission is to advance research, training, and education in artificial intelligence, machine learning, and data science applications for health and healthcare. A multidisciplinary, campus-spanning initiative housed in the Duke University School of Medicine, AI Health harnesses expertise and insights across multiple schools, centers, and institutes at Duke to bring to bear the power of AI, machine learning, and related quantitative fields on medicine, healthcare delivery, and the health of individuals and communities. 

Duke Health AI Evaluation and Governance (E&G) Program

The Duke Health AI Evaluation & Governance (E&G) Program fosters continuous advancement in research and framework development related to responsible health AI.  The program is committed to supporting initiatives that ensure the reliable selection, development, deployment, and utilization of AI technologies. E&G connects experts across Duke and engages in internal, national, and international collaborations.

Discovery AI

Discovery AI, housed in the Duke University School of Medicine and spanning multiple schools, departments and institutes across campus, advances the integration of artificial intelligence with fundamental biological research. The Center’s core mission is to fundamentally transform how biological systems are interrogated and engineered across all scales, from molecular to cellular to tissue. 

AI in the News

Nicole Calakos

What Comes Next: Neuroscience

Nicole Calakos, MD, PhD, is the Lincoln Financial Group Distinguished Professor of Neurobiology and specializes in synaptic physiology research and Parkinson’s disease and other movement disorders. She highlights the transformative impact of big data, AI, and cell modeling on neuroscience research, emphasizing the potential for advances in regenerative therapies and neural prostheses.
Kevin Saunders

What Comes Next: Vaccines

Dr. Kevin Saunders, a leader at the Duke Human Vaccine Institute, highlights the advancements in vaccine research, emphasizing the use of computational design, AI, and mRNA technology. Duke is at the forefront with significant progress in HIV, coronavirus, and cancer vaccines, and is developing pan-coronavirus and pan-influenza vaccines.
Tomi Akinyemiju

What Comes Next: Cancer Epidemiology and Population Health

Tomi Akinyemiju, PhD, is a professor in the Department of Population Health Sciences. She emphasizes the importance of prevention and health equity in epidemiology and advocates for personalized approaches, leveraging big data and AI for risk prediction, and ensuring equitable access to medical and policy solutions to address health disparities.
Raphael Valdivia

What Comes Next: Integrative Immunobiology

Dr. Raphael Valdivia, the Nanaline H. Duke Distinguished Professor of Molecular Genetics and Microbiology, emphasizes the need to understand the human immune system to address diseases like cancer and neurodegenerative disorders. His research focuses on leveraging AI and genetic engineering to guide immunity, highlighting Duke's strengths in transplant immunology and infectious disease research.
Nuo Li, PhD in his lab

One Way Your Brain Beats AI:  Learning Motor Tasks  

Research from Duke Science and Technology scholar Nuo Li, PhD, used a novel technique for tracking learning to reveal that the brain’s storage of certain memories is more complex and stable than previously thought.