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

New Methods (1166) Machine Learning (2193) Clinical Information and Decision Making (2029) Imaging Informatics (320) Decision Support for Health Professionals (1603) Artificial Intelligence (2280) Computer-Aided Diagnosis (270)

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 (3) 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

Conference Proceedings

  1. Tilak S, Joshi P. 2025 IEEE Pune Section International Conference (PuneCon). Evaluating the Impact of Handcrafted Feature Fusion with CNN Architectures on Ultrasound Based Muscle Health Assessment View