The applications of machine learning in plastic and reconstructive surgery: protocol of a systematic review.

ABSTRACT:

Background

Machine learning, a subset of artificial intelligence, is a set of models and methods that can automatically detect patterns in vast amounts of data, extract information and use it to perform various kinds of decision-making under uncertain conditions. This can assist surgeons in clinical decision-making by identifying patient cohorts that will benefit from surgery prior to treatment. The aim of this review is to evaluate the applications of machine learning in plastic and reconstructive surgery.

Methods

A literature review will be undertaken of EMBASE, MEDLINE and CENTRAL (1990 up to September 2019) to identify studies relevant for the review. Studies in which machine learning has been employed in the clinical setting of plastic surgery will be included. Primary

SUBMITTER: Mantelakis A 

PROVIDER: S-EPMC7047352 | biostudies-literature | 2020 Feb

REPOSITORIES: biostudies-literature