eDoctor: machine learning and the future of medicine

G S Handelman¹, H K Kok², R V Chandra^{3

4}, A H Razavi^{5

6}, M J Lee⁷, H Asadi^{3

8

9}

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.

PMID: 30102808
DOI: 10.1111/joim.12822

Free article

Review

eDoctor: machine learning and the future of medicine

G S Handelman et al. J Intern Med. 2018 Dec.

Free article

. 2018 Dec;284(6):603-619.

doi: 10.1111/joim.12822. Epub 2018 Sep 3.

Authors

G S Handelman¹, H K Kok², R V Chandra^{3

4}, A H Razavi^{5

6}, M J Lee⁷, H Asadi^{3

8

9}

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.

PMID: 30102808
DOI: 10.1111/joim.12822

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.

Keywords: artificial intelligence; machine learning; medicine; supervised machine learning; unsupervised machine learning.

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