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Applications of Machine Learning Using Electronic Medical Records in Spine Surgery.

Authors :
Schwartz JT
Gao M
Geng EA
Mody KS
Mikhail CM
Cho SK
Source :
Neurospine [Neurospine] 2019 Dec; Vol. 16 (4), pp. 643-653. Date of Electronic Publication: 2019 Dec 31.
Publication Year :
2019

Abstract

Developments in machine learning in recent years have precipitated a surge in research on the applications of artificial intelligence within medicine. Machine learning algorithms are beginning to impact medicine broadly, and the field of spine surgery is no exception. Electronic medical records are a key source of medical data that can be leveraged for the creation of clinically valuable machine learning algorithms. This review examines the current state of machine learning using electronic medical records as it applies to spine surgery. Studies across the electronic medical record data domains of imaging, text, and structured data are reviewed. Discussed applications include clinical prognostication, preoperative planning, diagnostics, and dynamic clinical assistance, among others. The limitations and future challenges for machine learning research using electronic medical records are also discussed.

Details

Language :
English
ISSN :
2586-6583
Volume :
16
Issue :
4
Database :
MEDLINE
Journal :
Neurospine
Publication Type :
Academic Journal
Accession number :
31905452
Full Text :
https://doi.org/10.14245/ns.1938386.193