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Identification of an ANCA-associated vasculitis cohort using deep learning and electronic health records.
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Rheumatology and Allergy Clinical Epidemiology Research Center and Division of Rheumatology, Allergy, and Immunology, and Mongan Institute, Department of Medicine, Massachusetts General Hospital Boston MA USA. Electronic address:
Background: ANCA-associated vasculitis (AAV) is a rare but serious disease. Traditional case-identification methods using claims data can be time-intensive and may miss important subgroups. We hypothesized that a deep learning model analyzing electronic health records (EHR) can more accurately identify AAV cases.
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JMIR Cancer
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View Article and Find Full Text PDFEffects of Acupoint Application on Postoperative Sore Throat in Adults Following General Endotracheal Anesthesia: A Randomized Placebo-controlled Study.
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Virol J
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Medi-X Pingshan, Southern University of Science and Technology, Shenzhen, Guangdong, 518118, China.
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