eDoctor: machine learning and the future of medicine

G. S. Handelman, H. K. Kok, R. V. Chandra, A. H. Razavi, M. J. Lee, H. Asadi

Research output: Contribution to journalReview ArticleResearchpeer-review

83 Citations (Scopus)

Abstract

Machine learning (ML) is a burgeoning field of medicine with huge resources being applied to fuse computer science and statistics to medical problems. Proponents of ML extol its ability to deal with large, complex and disparate data, often found within medicine and feel that ML is the future for biomedical research, personalized medicine, computer-aided diagnosis to significantly advance global health care. However, the concepts of ML are unfamiliar to many medical professionals and there is untapped potential in the use of ML as a research tool. In this article, we provide an overview of the theory behind ML, explore the common ML algorithms used in medicine including their pitfalls and discuss the potential future of ML in medicine.

Original languageEnglish
Pages (from-to)603-619
Number of pages17
JournalJournal of Internal Medicine
Volume284
Issue number6
DOIs
Publication statusPublished - 1 Dec 2018

Keywords

  • artificial intelligence
  • machine learning
  • medicine
  • supervised machine learning
  • unsupervised machine learning

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