Welcome to Stanford Medicine Center for Longevity and Healthy Aging
Fifteen years ago, 75-year-old Pakistani American Herma Ali was diagnosed with Stage III Breast Cancer at Stanford Medical Center. The Stanford breast cancer team endowed with the appropriate Pakistani cultural care of assessment and treatment for Herma’s disease. To respect Islamic traditional beliefs, they didn’t use the word “cancer” to elucidate the treatments and diagnoses…
The result of a well-done exploratory study is a hypothesis. That’s the formulation of the hypothesis. And it also results in having, giving you the information, you need to design a good study for that hypothesis. Questions like, what populations should I sample? How should I sample it? What measures should I take? How should…
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).
