Machine and deep learning-based clinical characteristics and laboratory markers for the prediction of sarcopenia.

Journal: Chinese medical journal
Published Date: Apr 20, 2023

Abstract

BACKGROUND: Sarcopenia is an age-related progressive skeletal muscle disorder involving the loss of muscle mass or strength and physiological function. Efficient and precise AI algorithms may play a significant role in the diagnosis of sarcopenia. In this study, we aimed to develop a machine learning model for sarcopenia diagnosis using clinical characteristics and laboratory indicators of aging cohorts.

Authors

  • He Zhang
    College of Natural Resources and Environment, Northwest A&F University, Yangling, 712100, Shaanxi, PR China; Key Laboratory of Plant Nutrition and the Agri-environment in Northwest China, Ministry of Agriculture and Rural Affairs, Yangling, 712100, Shaanxi, PR China.
  • Mengting Yin
    Department of Laboratory Medicine, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, China.
  • Qianhui Liu
  • Fei Ding
    Information Processing and Communication Technology Lab, Shanghai Institute of Satellite Engineering, Shanghai, China.
  • Lisha Hou
    Department of Geriatrics and National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, China.
  • Yiping Deng
    Department of Geriatrics and National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, China.
  • Tao Cui
    Department of Gynecology and Obstetrics, West China Second University Hospital, Sichuan University, Chengdu, Sichuan 610041, China.
  • Yixian Han
    Department of Gynecology and Obstetrics, West China Second University Hospital, Sichuan University, Chengdu, Sichuan 610041, China.
  • Weiguang Pang
    Key Laboratory of Intelligent Computing in Medical Image, Ministry of Education, Northeastern University, Shenyang, Liaoning 110819, China.
  • Wenbin Ye
    Department of Geriatrics, Xiamen Hospital of Traditional Chinese Medicine, Beijing University of Chinese Medicine, Xiamen, Fujian 361015, China.
  • Jirong Yue
    Department of Geriatrics and National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, China.
  • Yong He
    College of Biosystems Engineering and Food Science, Zhejiang Univ., Hangzhou, 310058, China.

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