An Artificial Intelligence Approach for Test-Free Identification of Sarcopenia.

ABSTRACT:

Background

The diagnosis of sarcopenia relies extensively on human and equipment resources and requires individuals to personally visit medical institutions. The objective of this study was to develop a test-free, self-assessable approach to identify sarcopenia by utilizing artificial intelligence techniques and representative real-world data.

Methods

This multicentre study enrolled 11 661 middle-aged and older adults from a national survey initialized in 2011. Follow-up data from the baseline cohort collected in 2013 (n = 9403) and 2015 (n = 10 356) were used for validation. Sarcopenia was retrospectively diagnosed using the Asian Working Group for Sarcopenia 2019 framework. Baseline age, sex, height, weight and 20 functional capacity (FC)-related binary indices (activities

SUBMITTER: Yin L 

PROVIDER: S-EPMC11634523 | biostudies-literature | 2024 Dec

REPOSITORIES: biostudies-literature