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eD octor: machine learning and the future of medicine
Author(s) -
Handelman G. S.,
Kok H. K.,
Chandra R. V.,
Razavi A. H.,
Lee M. J.,
Asadi H.
Publication year - 2018
Publication title -
journal of internal medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.625
H-Index - 160
eISSN - 1365-2796
pISSN - 0954-6820
DOI - 10.1111/joim.12822
Subject(s) - medicine , personalized medicine , field (mathematics) , alternative medicine , precision medicine , medline , artificial intelligence , health care , data science , medical education , bioinformatics , computer science , pathology , mathematics , political science , pure mathematics , law , economics , biology , economic growth
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.