eDoctor: machine learning and the future of medicine

被引：628

作者：

Handelman, G. S. ^{[1
]}

Kok, H. K. ^{[2
]}

Chandra, R. V. ^{[3
,4
]}

Razavi, A. H. ^{[5
,6
]}

Lee, M. J. ^{[7
,8
]}

Asadi, H. ^{[3
,9
,10
]}

机构：

[1] Royal Victoria Hosp, Belfast, Antrim, North Ireland

[2] Northern Hosp Radiol, Intervent Radiol Serv, Epping, NSW, Australia

[3] Monash Hlth, Intervent Neuroradiol Serv, Monash Imaging, Clayton, Vic, Australia

[4] Monash Univ, Fac Med Nursing & Hlth Sci, Clayton, Vic, Australia

[5] Univ Ottawa, Sch Informat Technol & Engn, Ottawa, ON, Canada

[6] BCE Corp Secur, Ottawa, ON, Canada

[7] Beaumont Hosp, Dept Radiol, Dublin, Ireland

[8] Royal Coll Surgeons Ireland, Dublin, Ireland

[9] Austin Hlth, Dept Radiol, Intervent Neuroradiol Serv, Heidelberg, Vic, Australia

[10] Deakin Univ, Sch Med, Fac Hlth, Waurn Ponds, Vic, Australia

来源：

JOURNAL OF INTERNAL MEDICINE | 2018年 / 284卷 / 06期

关键词：

artificial intelligence; machine learning; medicine; supervised machine learning; unsupervised machine learning; ARTIFICIAL-INTELLIGENCE; NEURAL-NETWORKS; LOGISTIC-REGRESSION; IMAGE RETRIEVAL; CANCER; CLASSIFICATION; PREDICTION; VALIDATION; DIAGNOSIS; MODELS;

D O I：

10.1111/joim.12822

中图分类号：

R5 [内科学];

学科分类号：

1002 ; 100201 ;

摘要：

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.

引用

页码：603 / 619

页数：17

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