Machine Learning Applications in Endocrinology and Metabolism Research: An Overview.

ABSTRACT: Machine learning (ML) applications have received extensive attention in endocrinology research during the last decade. This review summarizes the basic concepts of ML and certain research topics in endocrinology and metabolism where ML principles have been actively deployed. Relevant studies are discussed to provide an overview of the methodology, main findings, and limitations of ML, with the goal of stimulating insights into future research directions. Clear, testable study hypotheses stem from unmet clinical needs, and the management of data quality (beyond a focus on quantity alone), open collaboration between clinical experts and ML engineers, the development of interpretable high-performance ML models beyond the black-box nature of some algorithms, and a creative environment are the

SUBMITTER: Hong N 

PROVIDER: S-EPMC7090299 | biostudies-literature | 2020 Mar

REPOSITORIES: biostudies-literature