Machine learning will dramatically improve health care. There are already myriad impactful ML health care applications from imaging to predicting readmissions to the back office. But there are also high-profile, expensive efforts that have not achieved their goals.
In the authors’ collective roles as the CEO of a care delivery analytics business, tech-driven clinicians, and the leader of tech innovation at a major health system, they have developed and used dozens of ML applications. Many of these have succeeded, but others have not. From these experiences they have identified three common myths that exist around ML in health care.Accelerate your career with Harvard ManageMentor®.
research group which uses machine learning to develop predictive models in surgery. He is also an associate professor of orthopaedic surgery at Harvard Medical School and the chief of spine surgery at Massachusetts General Hospital., MD, is the president of Mayo Clinic Platform, where he leads a portfolio of new digital platform businesses focused on transforming health.
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