Deep-learning model for predicting physical fitness in possible sarcopenia: analysis of the Korean physical fitness award from 2010 to 2023.

Journal: Frontiers in public health

PMID: 37614451

Abstract

INTRODUCTION: Physical fitness is regarded as a significant indicator of sarcopenia. This study aimed to develop and evaluate a deep-learning model for predicting the decline in physical fitness due to sarcopenia in individuals with potential sarcopenia.

Authors

Jun-Hyun Bae

Able-Art Sport, Department of Theory, Hyupsung University, Hwaseong, Gyeonggi-do, Republic of Korea.
Ji-Won Seo

Department of Physical Education, Seoul National University, Seoul, Republic of Korea.
Dae Young Kim

Senior Exercise Rehabilitation Laboratory, Department of Gerokinesiology, Kyungil University, Gyeongsan, Gyeongsangbuk-do, Republic of Korea.

Keywords

Aged Deep Learning Female Humans Male Neural Networks, Computer Physical Fitness Republic of Korea Sarcopenia

External Resources

View on PubMed Access via DOI PubMed (37614451)

Deep-learning model for predicting physical fitness in possible sarcopenia: analysis of the Korean physical fitness award from 2010 to 2023.

Abstract

Authors

Keywords

External Resources

Popular Topics

Recent Journals