A scoping review of artificial intelligence applications in thoracic surgery.

ABSTRACT:

Objectives

Machine learning (ML) has great potential, but there are few examples of its implementation improving outcomes. The thoracic surgeon must be aware of pertinent ML literature and how to evaluate this field for the safe translation to patient care. This scoping review provides an introduction to ML applications specific to the thoracic surgeon. We review current applications, limitations and future directions.

Methods

A search of the PubMed database was conducted with inclusion requirements being the use of an ML algorithm to analyse patient information relevant to a thoracic surgeon and contain sufficient details on the data used, ML methods and results. Twenty-two papers met the criteria and were reviewed using a methodological quality rubric.

Results

ML de

SUBMITTER: Seastedt KP 

PROVIDER: S-EPMC8932394 | biostudies-literature | 2022 Jan

REPOSITORIES: biostudies-literature