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      eDoctor: machine learning and the future of medicine.

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          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.

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          Author and article information

          Journal
          J. Intern. Med.
          Journal of internal medicine
          Wiley
          1365-2796
          0954-6820
          Dec 2018
          : 284
          : 6
          Affiliations
          [1 ] Royal Victoria Hospital, Belfast, UK.
          [2 ] Interventional Radiology Service, Northern Hospital Radiology, Epping, Vic, Australia.
          [3 ] Interventional Neuroradiology Service, Monash Imaging, Monash Health, Clayton, Vic, Australia.
          [4 ] Faculty of Medicine, Nursing and Health Sciences, Monash University, Clayton, Vic, Australia.
          [5 ] School of Information Technology and Engineering, University of Ottawa, Ottawa, ON, Canada.
          [6 ] BCE Corporate Security, Ottawa, ON, Canada.
          [7 ] Department of Radiology, Beaumont Hospital and Royal College of Surgeons in Ireland, Dublin, Ireland.
          [8 ] Department of Radiology, Interventional Neuroradiology Service, Austin Health, Heidelberg, Vic, Australia.
          [9 ] School of Medicine, Faculty of Health, Deakin University, Waurn Ponds, Vic, Australia.
          Article
          10.1111/joim.12822
          30102808
          5f3ed11f-2320-464f-a87e-7ffda21bdbf5
          History

          artificial intelligence,machine learning,medicine,supervised machine learning,unsupervised machine learning

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