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Predicting hospital readmission risk in patients with COVID-19: A machine learning approach.

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第一作者： Mohammad Reza,Afrash

第一单位： Department of Health Information Technology and Management, School of Allied Medical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran.

作者： Mohammad Reza,Afrash ^[1] ; Hadi,Kazemi-Arpanahi ^[2] ; Mostafa,Shanbehzadeh ^[3] ; Raoof,Nopour ^[4] ; Esmat,Mirbagheri ^[5]

作者单位： Department of Health Information Technology and Management, School of Allied Medical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran. ^[1] Department of Health Information Technology, Abadan Faculty of Medical Sciences, Abadan, Iran.;Student Research Committee, Abadan Faculty of Medical Sciences, Abadan, Iran. ^[2] Department of Health Information Technology, School of Paramedical, Ilam University of Medical Sciences, Ilam, Iran. ^[3] Department of Health Information Management, Student Research Committee, School of Health Management and Information Sciences Branch, Iran University of Medical Sciences, Tehran, Iran. ^[4] Department of Health Information Management, School of Health Management and Information Sciences, Iran University of Medical Sciences, Tehran, Iran. ^[5]

关键词 AUC, Area under the curve Artificial intelligent CDSS, Clinical Decision Support Systems COVID-19 COVID-19, Coronavirus disease 2019 CRISP, Cross-Industry Standard Process Coronavirus HGB, Hist Gradient Boosting LASSO, Least Absolute Shrinkage and Selection Operator ML, Machine learning MLP, Multi-Layered Perceptron Machine learning Readmission SVM, Support Vector Machine XGBoost, Extreme Gradient Boosting

DOI 10.1016/j.imu.2022.100908

PMID 35280933

发布时间 2024-09-13

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