This paper is in the following e-collection/theme issue:

New Methods (1134) Machine Learning (2076) Clinical Information and Decision Making (1915) Imaging Informatics (302) Decision Support for Health Professionals (1539) Artificial Intelligence (2129) Computer-Aided Diagnosis (251)

Published on in Vol 27 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/70545, first published .
Diagnosis of Sarcopenia Using Convolutional Neural Network Models Based on Muscle Ultrasound Images: Prospective Multicenter Study

Diagnosis of Sarcopenia Using Convolutional Neural Network Models Based on Muscle Ultrasound Images: Prospective Multicenter Study

Diagnosis of Sarcopenia Using Convolutional Neural Network Models Based on Muscle Ultrasound Images: Prospective Multicenter Study

Authors of this article:

Zi-Tong Chen1 Author Orcid Image ;   Xiao-Long Li1 Author Orcid Image ;   Feng-Shan Jin2, 3, 4 Author Orcid Image ;   Yi-Lei Shi5 Author Orcid Image ;   Lei Zhang5 Author Orcid Image ;   Hao-Hao Yin1 Author Orcid Image ;   Yu-Li Zhu1 Author Orcid Image ;   Xin-Yi Tang6 Author Orcid Image ;   Xi-Yuan Lin1 Author Orcid Image ;   Bei-Lei Lu1 Author Orcid Image ;   Qun Wang1 Author Orcid Image ;   Li-Ping Sun2, 3, 4 Author Orcid Image ;   Xiao-Xiang Zhu7 Author Orcid Image ;   Li Qiu6 Author Orcid Image ;   Hui-Xiong Xu1 Author Orcid Image ;   Le-Hang Guo2, 3, 4 Author Orcid Image
Article Authors Cited by (2) Tweetations Metrics

Journals

  1. Zhang M, Zhong M, Cheng Y, Zhang T. Intelligent Prediction Platform for Sepsis Risk Based on Real-Time Dynamic Temporal Features: Design Study. JMIR Medical Informatics 2025;13:e74940 View
  2. Filippucci E, Cipolletta E. Automated ultrasound in rheumatology: the dawn of a new era. RMD Open 2025;11(4):e006273 View