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August 8, 2017

Unintended Consequences of Machine Learning in Medicine

Author Affiliations
  • 1Department of Informatics, University of Milano-Bicocca, Milan, Italy
  • 2IRCCS Istituto Ortopedico Galeazzi, Milan, Italy
  • 3Centro Studi Medicina Avanzata, Florence, Italy
JAMA. 2017;318(6):517-518. doi:10.1001/jama.2017.7797

Over the past decade, machine learning techniques have made substantial advances in many domains. In health care, global interest in the potential of machine learning has increased; for example, a deep learning algorithm has shown high accuracy in detecting diabetic retinopathy.1 There have been suggestions that machine learning will drive changes in health care within a few years, specifically in medical disciplines that require more accurate prognostic models (eg, oncology) and those based on pattern recognition (eg, radiology and pathology).