Performance Evaluation of Machine Learning Algorithms for Sarcopenia Diagnosis in Older Adults.

ABSTRACT:

Background

Sarcopenia is a progressive and generalized skeletal muscle disorder. Early diagnosis is necessary to reduce the adverse effects and consequences of sarcopenia, which can help prevent and manage it in a timely manner. The aim of this study was to identify the important risk factors for sarcopenia diagnosis and compare the performance of machine learning (ML) algorithms in the early detection of potential sarcopenia.

Methods

A cross-sectional design was employed for this study, involving 160 participants aged 65 years and over who resided in a community. ML algorithms were applied by selecting 11 features-sex, age, BMI, presence of hypertension, presence of diabetes mellitus, SARC-F score, MNA score, calf circumference (CC), gait speed, handgrip strength (HS), and

SUBMITTER: Ozgur S 

PROVIDER: S-EPMC10572141 | biostudies-literature | 2023 Oct

REPOSITORIES: biostudies-literature