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

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Title: Diagnosis of Sarcopenia Using Convolutional Neural Network Models Based on Muscle Ultrasound Images: Prospective Multicenter Study.
Authors: Chen ZT; Department of Ultrasound, Zhongshan Hospital, Institute of Ultrasound in Medicine and Engineering, Fudan University, Shanghai, China., Li XL; Department of Ultrasound, Zhongshan Hospital, Institute of Ultrasound in Medicine and Engineering, Fudan University, Shanghai, China., Jin FS; Department of Medical Ultrasound, Shanghai Tenth People's Hospital, Shanghai, China.; Ultrasound Research and Education Institute, Tongji University School of Medicine, Shanghai, China.; Shanghai Engineering Research Center of Ultrasound Diagnosis and Treatment, Shanghai, China., Shi YL; MedAI Technology (Wuxi) Co, Ltd, Wuxi, China., Zhang L; MedAI Technology (Wuxi) Co, Ltd, Wuxi, China., Yin HH; Department of Ultrasound, Zhongshan Hospital, Institute of Ultrasound in Medicine and Engineering, Fudan University, Shanghai, China., Zhu YL; Department of Ultrasound, Zhongshan Hospital, Institute of Ultrasound in Medicine and Engineering, Fudan University, Shanghai, China., Tang XY; Department of Medical Ultrasound, West China Hospital of Sichuan University, Chengdu, China., Lin XY; Department of Ultrasound, Zhongshan Hospital, Institute of Ultrasound in Medicine and Engineering, Fudan University, Shanghai, China., Lu BL; Department of Ultrasound, Zhongshan Hospital, Institute of Ultrasound in Medicine and Engineering, Fudan University, Shanghai, China., Wang Q; Department of Ultrasound, Zhongshan Hospital, Institute of Ultrasound in Medicine and Engineering, Fudan University, Shanghai, China., Sun LP; Department of Medical Ultrasound, Shanghai Tenth People's Hospital, Shanghai, China.; Ultrasound Research and Education Institute, Tongji University School of Medicine, Shanghai, China.; Shanghai Engineering Research Center of Ultrasound Diagnosis and Treatment, Shanghai, China., Zhu XX; Chair of Data Science in Earth Observation, Technical University of Munich, Munich, Germany., Qiu L; Department of Medical Ultrasound, West China Hospital of Sichuan University, Chengdu, China., Xu HX; Department of Ultrasound, Zhongshan Hospital, Institute of Ultrasound in Medicine and Engineering, Fudan University, Shanghai, China., Guo LH; Department of Medical Ultrasound, Shanghai Tenth People's Hospital, Shanghai, China.; Ultrasound Research and Education Institute, Tongji University School of Medicine, Shanghai, China.; Shanghai Engineering Research Center of Ultrasound Diagnosis and Treatment, Shanghai, China.
Source: Journal of medical Internet research [J Med Internet Res] 2025 May 06; Vol. 27, pp. e70545. Date of Electronic Publication: 2025 May 06.
Publication Type: Journal Article; Multicenter Study
Journal Info: Publisher: JMIR Publications Country of Publication: Canada NLM ID: 100959882 Publication Model: Electronic Cited Medium: Internet ISSN: 1438-8871 (Electronic) Linking ISSN: 14388871 NLM ISO Abbreviation: J Med Internet Res Subsets: MEDLINE
Database: MEDLINE Ultimate
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  Data: Diagnosis of Sarcopenia Using Convolutional Neural Network Models Based on Muscle Ultrasound Images: Prospective Multicenter Study.
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  Data: <searchLink fieldCode="AU" term="%22Chen+ZT%22">Chen ZT</searchLink>; Department of Ultrasound, Zhongshan Hospital, Institute of Ultrasound in Medicine and Engineering, Fudan University, Shanghai, China.<br /><searchLink fieldCode="AU" term="%22Li+XL%22">Li XL</searchLink>; Department of Ultrasound, Zhongshan Hospital, Institute of Ultrasound in Medicine and Engineering, Fudan University, Shanghai, China.<br /><searchLink fieldCode="AU" term="%22Jin+FS%22">Jin FS</searchLink>; Department of Medical Ultrasound, Shanghai Tenth People's Hospital, Shanghai, China.; Ultrasound Research and Education Institute, Tongji University School of Medicine, Shanghai, China.; Shanghai Engineering Research Center of Ultrasound Diagnosis and Treatment, Shanghai, China.<br /><searchLink fieldCode="AU" term="%22Shi+YL%22">Shi YL</searchLink>; MedAI Technology (Wuxi) Co, Ltd, Wuxi, China.<br /><searchLink fieldCode="AU" term="%22Zhang+L%22">Zhang L</searchLink>; MedAI Technology (Wuxi) Co, Ltd, Wuxi, China.<br /><searchLink fieldCode="AU" term="%22Yin+HH%22">Yin HH</searchLink>; Department of Ultrasound, Zhongshan Hospital, Institute of Ultrasound in Medicine and Engineering, Fudan University, Shanghai, China.<br /><searchLink fieldCode="AU" term="%22Zhu+YL%22">Zhu YL</searchLink>; Department of Ultrasound, Zhongshan Hospital, Institute of Ultrasound in Medicine and Engineering, Fudan University, Shanghai, China.<br /><searchLink fieldCode="AU" term="%22Tang+XY%22">Tang XY</searchLink>; Department of Medical Ultrasound, West China Hospital of Sichuan University, Chengdu, China.<br /><searchLink fieldCode="AU" term="%22Lin+XY%22">Lin XY</searchLink>; Department of Ultrasound, Zhongshan Hospital, Institute of Ultrasound in Medicine and Engineering, Fudan University, Shanghai, China.<br /><searchLink fieldCode="AU" term="%22Lu+BL%22">Lu BL</searchLink>; Department of Ultrasound, Zhongshan Hospital, Institute of Ultrasound in Medicine and Engineering, Fudan University, Shanghai, China.<br /><searchLink fieldCode="AU" term="%22Wang+Q%22">Wang Q</searchLink>; Department of Ultrasound, Zhongshan Hospital, Institute of Ultrasound in Medicine and Engineering, Fudan University, Shanghai, China.<br /><searchLink fieldCode="AU" term="%22Sun+LP%22">Sun LP</searchLink>; Department of Medical Ultrasound, Shanghai Tenth People's Hospital, Shanghai, China.; Ultrasound Research and Education Institute, Tongji University School of Medicine, Shanghai, China.; Shanghai Engineering Research Center of Ultrasound Diagnosis and Treatment, Shanghai, China.<br /><searchLink fieldCode="AU" term="%22Zhu+XX%22">Zhu XX</searchLink>; Chair of Data Science in Earth Observation, Technical University of Munich, Munich, Germany.<br /><searchLink fieldCode="AU" term="%22Qiu+L%22">Qiu L</searchLink>; Department of Medical Ultrasound, West China Hospital of Sichuan University, Chengdu, China.<br /><searchLink fieldCode="AU" term="%22Xu+HX%22">Xu HX</searchLink>; Department of Ultrasound, Zhongshan Hospital, Institute of Ultrasound in Medicine and Engineering, Fudan University, Shanghai, China.<br /><searchLink fieldCode="AU" term="%22Guo+LH%22">Guo LH</searchLink>; Department of Medical Ultrasound, Shanghai Tenth People's Hospital, Shanghai, China.; Ultrasound Research and Education Institute, Tongji University School of Medicine, Shanghai, China.; Shanghai Engineering Research Center of Ultrasound Diagnosis and Treatment, Shanghai, China.
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  Data: <searchLink fieldCode="JN" term="%22100959882%22">Journal of medical Internet research</searchLink> [J Med Internet Res] 2025 May 06; Vol. 27, pp. e70545. <i>Date of Electronic Publication: </i>2025 May 06.
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  Data: Journal Article; Multicenter Study
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  Data: <i>Publisher: </i><searchLink fieldCode="PB" term="%22JMIR+Publications%22">JMIR Publications </searchLink><i>Country of Publication: </i>Canada <i>NLM ID: </i>100959882 <i>Publication Model: </i>Electronic <i>Cited Medium: </i>Internet <i>ISSN: </i>1438-8871 (Electronic) <i>Linking ISSN: </i><searchLink fieldCode="IS" term="%2214388871%22">14388871 </searchLink><i>NLM ISO Abbreviation: </i>J Med Internet Res <i>Subsets: </i>MEDLINE
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      – TitleFull: Diagnosis of Sarcopenia Using Convolutional Neural Network Models Based on Muscle Ultrasound Images: Prospective Multicenter Study.
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            – D: 06
              M: 05
              Text: 2025 May 06
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