Welcome to Stanford Medicine Center for Longevity and Healthy Aging
Dr. Ogungbe is an Assistant Professor at the Johns Hopkins School of Nursing and Johns Hopkins Bloomberg School of Public Health, and an Associate Faculty the Welch Center for Prevention, Epidemiology, and Clinical Research. Her research goals are to improve cardiometabolic outcomes among populations experiencing social marginalization, including aging populations. Through her research and collaborations, Dr. Ogungbe aims…
Michelle Lin, MD, MPH, MS is an Associate Professor of Emergency Medicine whose work is driven by a strong belief that emergency departments can be a key partner in improving care for older adults—in particular, for those who experience barriers to accessing care in other settings due to adverse social and functional factors. Her work…
Julia Adler-Milstein, PhD1; Jonathan H. Chen, MD, PhD; Gurpreet Dhaliwal, MD
Improving the diagnostic process is a quality and safety priority.With the digitization of health records and rapid expansion of health data, the cognitive demand on the diagnostician has increased. The use of artificial intelligence (AI) to assist human cognition has the potential to reduce this demand and associated diagnostic errors. However, current AI tools have not realized this potential, due in part to the long-standing focus of these tools on predicting final diagnostic labels instead of helping clinicians navigate the dynamic refinement process of diagnosis. This Viewpoint highlights the importance of shifting the role of diagnostic AI from predicting labels to “wayfinding” (interpreting context and providing cues that guide the diagnostician).
