Machine learning in endocrinology: current applications and future perspectives.

ABSTRACT:

Purpose

In recent years, endocrinology research has increasingly focused on machine learning (ML) applications. ML offers the possibility of utilizing large data sets and extracting imperceptible patterns. It might contribute in optimizing healthcare outcomes and unveiling new understandings of the intricate mechanisms of endocrine disorders. This review covers the basic aspects of ML and highlights specific areas of endocrinology with potential of ML application.

Methods

This narrative review with a systematic literature search comprises studies on endocrine conditions with ML methods used in statistical analysis, published between January 2000 and December 2024.

Results

A total of 1130 studies were analyzed. Thyroid-related research was the most prevalent, followed

SUBMITTER: Kaminska M 

PROVIDER: S-EPMC12572088 | biostudies-literature | 2025 Nov

REPOSITORIES: biostudies-literature