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Comparison of Machine Learning Algorithms for Predicting Hospital Readmissions and Worsening Heart Failure Events in Patients With Heart Failure With Reduced Ejection Fraction: Modeling Study.

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第一作者： Boshu,Ru

第一单位： Merck & Co, Inc, Rahway, NJ, United States.

作者： Boshu,Ru ^[1] ; Xi,Tan ^[1] ; Yu,Liu ^[1] ; Kartik,Kannapur ^[2] ; Dheepan,Ramanan ^[2] ; Garin,Kessler ^[3] ; Dominik,Lautsch ^[1] ; Gregg,Fonarow ^[4]

作者单位： Merck & Co, Inc, Rahway, NJ, United States. ^[1] Amazon Web Services Inc, Seattle, WA, United States. ^[2] Amazon Web Services Inc, Seattle, WA, United States.;School of Continuing Studies, Georgetown University, Washington, DC, United States. ^[3] Ahmanson-UCLA Cardiomyopathy Center, University of California, Los Angeles, Los Angeles, CA, United States. ^[4]

关键词 BERT Bidirectional Encoder Representations From Transformers clinical registry deep learning heart failure heart failure with reduced ejection fraction hospital readmission machine learning medical claims real-world data worsening heart failure event

DOI 10.2196/41775

PMID 37067873

发布时间 2023-07-10

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Comparison of Machine Learning Algorithms for Predicting Hospital Readmissions and Worsening Heart Failure Events in Patients With Heart Failure With Reduced Ejection Fraction: Modeling Study.

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Comparison of Machine Learning Algorithms for Predicting Hospital Readmissions and Worsening Heart Failure Events in Patients With Heart Failure With Reduced Ejection Fraction: Modeling Study.

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