Feature Selection and Machine Learning Approaches for Detecting Sarcopenia Through Predictive Modeling

• Published in: Mathematics (Basel) Vol. 13; no. 1; p. 98
• Main Authors: Tukhtaev, Akhrorbek, Turimov, Dilmurod, Kim, Jiyoun, Kim, Wooseong
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.01.2025
• Subjects: Accuracy; Aging; Algorithms; Artificial intelligence; CatBoost; Clinical outcomes; Credit scoring; Datasets; Deep learning; Diagnosis; Exercise; Feature selection; LIME; Literature reviews; Machine learning; Medical imaging; Musculoskeletal system; Older people; Optimization techniques; Prediction models; random forest; Sarcopenia; South Korea

Sarcopenia is an age-associated condition characterized by a muscle mass and function decline. This condition poses significant health risks for the elderly. This study developed a machine-learning model to predict sarcopenia using data from 664 participants. Key features were identified using the L...