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Novel Machine Learning Approach to Predict and Personalize Length of Stay for Patients Admitted with Syncope from the Emergency Department.

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第一作者： Sangil,Lee

第一单位： Department of Emergency Medicine, Carver College of Medicine, University of Iowa, 200 Hawkins Drive, Iowa City, IA 52242, USA.

作者： Sangil,Lee ^[1] ; Avinash,Reddy Mudireddy ^[2] ; Deepak,Kumar Pasupula ^[3] ; Mehul,Adhaduk ^[4] ; E John,Barsotti ^[5] ; Milan,Sonka ^[2] ; Giselle M,Statz ^[6] ; Tyler,Bullis ^[4] ; Samuel L,Johnston ^[6] ; Aron Z,Evans ^[4] ; Brian,Olshansky ^[6] ; Milena A,Gebska ^[6]

作者单位： Department of Emergency Medicine, Carver College of Medicine, University of Iowa, 200 Hawkins Drive, Iowa City, IA 52242, USA. ^[1] The Iowa Initiative of Artificial Intelligence, University of Iowa, 103 South Capitol Street, Iowa City, IA 52242, USA. ^[2] Division of Cardiology, Mercy One North Iowa Heart Center, 250 S Crescent Dr, Mason City, IA 50401, USA. ^[3] Department of Internal Medicine, Carver College of Medicine, University of Iowa, 200 Hawkins Drive, Iowa City, IA 52242, USA. ^[4] Department of Epidemiology, College of Public Health, University of Iowa, 145 N. Riverside Drive, Iowa City, IA 52242, USA. ^[5] Division of Cardiovascular Medicine, Carver College of Medicine, University of Iowa, 200 Hawkins Drive, Iowa City, IA 52242, USA. ^[6]

关键词 artificial intelligence length of stay machine learning prediction syncope

DOI 10.3390/jpm13010007

PMID 36675668

发布时间 2023-03-08

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Journal of personalized medicine

2022年13卷1期

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Journal of personalized medicine

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Novel Machine Learning Approach to Predict and Personalize Length of Stay for Patients Admitted with Syncope from the Emergency Department.

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Novel Machine Learning Approach to Predict and Personalize Length of Stay for Patients Admitted with Syncope from the Emergency Department.

Journal of personalized medicine

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