A Machine Learning Model for Predicting Sarcopenia Among Middle-Aged Adults: Development and External Validation.

ABSTRACT:

Background

Sarcopenia is a common muscle disorder in older adults, and its early identification and management in middle-aged populations are essential for ensuring a healthier later life. Detecting sarcopenia at an earlier stage may reduce the future burden on health care systems and enhance the quality of life in older adults. Machine learning (ML) models can evaluate large datasets, identify essential variables, and find complicated correlations between input variables. However, using ML models to detect sarcopenia remains an unsatisfied need.

Objective

This study aimed to develop and externally validate an ML model to predict sarcopenia risk among middle-aged adults using a nationally representative dataset.

Methods

We analyzed data from 1926 participants aged 40

SUBMITTER: Chong HJ 

PROVIDER: S-EPMC12423610 | biostudies-literature | 2025 Aug

REPOSITORIES: biostudies-literature