Machine-learning classifier models for predicting sarcopenia in the elderly based on physical factors.

Journal: Geriatrics & gerontology international
PMID:

Abstract

AIM: As the size of the elderly population gradually increases, musculoskeletal disorders, such as sarcopenia, are increasing. Diagnostic techniques such as X-rays, computed tomography, and magnetic resonance imaging are used to predict and diagnose sarcopenia, and methods using machine learning are gradually increasing. This study aimed to create a model that can predict sarcopenia using physical characteristics and activity-related variables without medical diagnostic equipment, such as imaging equipment, for the elderly aged 60 years or older.

Authors

  • Jun-Hee Kim
    Laboratory of KEMA AI Research (KAIR), Department of Physical Therapy, College of Software and Digital Healthcare Convergence, Yonsei University, Wonju, South Korea.