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Deep learning-aided diagnosis of acute abdominal aortic dissection by ultrasound images.

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Title: Deep learning-aided diagnosis of acute abdominal aortic dissection by ultrasound images.
Authors: Lin Z; Ultrasound Department of The Second Affiliated Hospital, School of Medicine, The Chinese University of Hong Kong, Shenzhen & Longgang District People's Hospital of Shenzhen, Shenzhen, China., Zheng J; Ultrasound Department of The Second Affiliated Hospital, School of Medicine, The Chinese University of Hong Kong, Shenzhen & Longgang District People's Hospital of Shenzhen, Shenzhen, China., Deng Y; Department of Research and Development, Yizhun Medical AI Co. Ltd, Beijing, China., Du L; Department of Radiology, Huazhong University of Science and Technology Union Shenzhen Hospital, Shenzhen, China., Liu F; Ultrasound Department of The Second Affiliated Hospital, School of Medicine, The Chinese University of Hong Kong, Shenzhen & Longgang District People's Hospital of Shenzhen, Shenzhen, China., Li Z; Department of Ultrasound, Shenzhen Second People's Hospital, The First Affiliated Hospital of Shenzhen University, Shenzhen, China. lizhyi009@163.com.
Source: Emergency radiology [Emerg Radiol] 2025 Apr; Vol. 32 (2), pp. 233-239. Date of Electronic Publication: 2025 Jan 17.
Publication Type: Journal Article
Journal Info: Publisher: Springer-Verlag New York Inc Country of Publication: United States NLM ID: 9431227 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1438-1435 (Electronic) Linking ISSN: 10703004 NLM ISO Abbreviation: Emerg Radiol Subsets: MEDLINE
Database: MEDLINE Ultimate
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  Data: Deep learning-aided diagnosis of acute abdominal aortic dissection by ultrasound images.
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  Data: <searchLink fieldCode="AU" term="%22Lin+Z%22">Lin Z</searchLink>; Ultrasound Department of The Second Affiliated Hospital, School of Medicine, The Chinese University of Hong Kong, Shenzhen & Longgang District People's Hospital of Shenzhen, Shenzhen, China.<br /><searchLink fieldCode="AU" term="%22Zheng+J%22">Zheng J</searchLink>; Ultrasound Department of The Second Affiliated Hospital, School of Medicine, The Chinese University of Hong Kong, Shenzhen & Longgang District People's Hospital of Shenzhen, Shenzhen, China.<br /><searchLink fieldCode="AU" term="%22Deng+Y%22">Deng Y</searchLink>; Department of Research and Development, Yizhun Medical AI Co. Ltd, Beijing, China.<br /><searchLink fieldCode="AU" term="%22Du+L%22">Du L</searchLink>; Department of Radiology, Huazhong University of Science and Technology Union Shenzhen Hospital, Shenzhen, China.<br /><searchLink fieldCode="AU" term="%22Liu+F%22">Liu F</searchLink>; Ultrasound Department of The Second Affiliated Hospital, School of Medicine, The Chinese University of Hong Kong, Shenzhen & Longgang District People's Hospital of Shenzhen, Shenzhen, China.<br /><searchLink fieldCode="AU" term="%22Li+Z%22">Li Z</searchLink>; Department of Ultrasound, Shenzhen Second People's Hospital, The First Affiliated Hospital of Shenzhen University, Shenzhen, China. lizhyi009@163.com.
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  Data: <searchLink fieldCode="JN" term="%229431227%22">Emergency radiology</searchLink> [Emerg Radiol] 2025 Apr; Vol. 32 (2), pp. 233-239. <i>Date of Electronic Publication: </i>2025 Jan 17.
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        Value: 10.1007/s10140-025-02311-y
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              Text: 2025 Apr
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