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Featured Clinical Reviews

Diagnostic Excellence
December 9, 2021

Next-Generation Artificial Intelligence for Diagnosis: From Predicting Diagnostic Labels to “Wayfinding”

Author Affiliations
  • 1Department of Medicine, University of California, San Francisco
  • 2Division of Hospital Medicine, University of California, San Francisco
  • 3Stanford Center for Biomedical Informatics Research, Stanford University, Stanford, California
  • 4Division of Hospital Medicine, Stanford University, Stanford, California
  • 5Medical Service, San Francisco Veterans Affairs Medical Center, San Francisco, California
JAMA. 2021;326(24):2467-2468. doi:10.1001/jama.2021.22396

Improving the diagnostic process is a quality and safety priority.1 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).

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