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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

For example, Chen et al [23] developed a diagnostic model for sarcopenia based on age, cross-sectional area changes, and shear wave elasticity value changes, yielding an AUC of 0.883. Tang et al [24] developed an ultrasound-derived muscle assessment system based on muscle thickness, handgrip strength, and gait speed. The system had an overall diagnostic sensitivity of 92.7% and a specificity of 91% for sarcopenia.

Zi-Tong Chen, Xiao-Long Li, Feng-Shan Jin, Yi-Lei Shi, Lei Zhang, Hao-Hao Yin, Yu-Li Zhu, Xin-Yi Tang, Xi-Yuan Lin, Bei-Lei Lu, Qun Wang, Li-Ping Sun, Xiao-Xiang Zhu, Li Qiu, Hui-Xiong Xu, Le-Hang Guo

J Med Internet Res 2025;27:e70545

Online Health Information–Seeking Behaviors Among the Chongqing Population: Cross-Sectional Questionnaire Study

Online Health Information–Seeking Behaviors Among the Chongqing Population: Cross-Sectional Questionnaire Study

Most participants (95.3%, 13,793/14,466) were of Han Chinese ethnicity. The percentage of participants residing in urban areas was 69.7% (10,090/14,466). Overall, 47.1% (6813/14,466) of participants were college graduates or had a higher level of education. The participants spanned all occupation groups.

Honghui Rong, Lu Lu, Miao He, Tian Guo, Xian Li, Qingliu Tao, Yixin Li, Chuanfen Zheng, Ling Zhang, Fengju Li, Dali Yi, Enyu Lei, Ting Luo, Qinghua Yang, Ji-an Chen

JMIR Form Res 2025;9:e56028