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Viewpoint | Innovations in Health Care Delivery

Machine Learning and the Profession of Medicine

Alison M. Darcy, PhD1; Alan K. Louie, MD1; Laura Weiss Roberts, MD, MA1
[+] Author Affiliations
1Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, California
JAMA. 2016;315(6):551-552. doi:10.1001/jama.2015.18421.
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This Viewpoint discusses the opportunities and ethical implications of using machine learning technologies, which can rapidly collect and learn from large amounts of personal data, to provide individalized patient care.

Must a physician be human? A new computer, “Ellie,” developed at the Institute for Creative Technologies, asks questions as a clinician might, such as “How easy is it for you to get a good night’s sleep?” Ellie then analyzes the patient’s verbal responses, facial expressions, and vocal intonations, possibly detecting signs of posttraumatic stress disorder, depression, or other medical conditions. In a randomized study, 239 probands were told that Ellie was “controlled by a human” or “a computer program.” Those believing the latter revealed more personal material to Ellie, based on blind ratings and self-reports.1 In China, millions of people turn to Microsoft’s chatbot, “Xiaoice,”2 when they need a “sympathetic ear,” despite knowing that Xiaoice is not human. Xiaoice develops a specially attuned personality and sense of humor by methodically mining the Internet for real text conversations. Xiaoice also learns about users from their reactions over time and becomes sensitive to their emotions, modifying responses accordingly, all without human instruction. Ellie and Xiaoice are the result of machine learning technology.

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The American Medical Association is accredited by the Accreditation Council for Continuing Medical Education to provide continuing medical education for physicians. The AMA designates this journal-based CME activity for a maximum of 1 AMA PRA Category 1 CreditTM per course. Physicians should claim only the credit commensurate with the extent of their participation in the activity. Physicians who complete the CME course and score at least 80% correct on the quiz are eligible for AMA PRA Category 1 CreditTM.
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