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Machine Learning-Enabled Clinical Information Systems Using Fast Healthcare Interoperability Resources Data Standards: Scoping Review.

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第一作者： Jeremy A,Balch

第一单位： Department of Surgery, University of Florida Health, Gainesville, FL, United States.;Intelligent Critical Care Center, University of Florida, Gainesville, FL, United States.

作者： Jeremy A,Balch ^[1] ; Matthew M,Ruppert ^[2] ; Tyler J,Loftus ^[1] ; Ziyuan,Guan ^[2] ; Yuanfang,Ren ^[2] ; Gilbert R,Upchurch ^[3] ; Tezcan,Ozrazgat-Baslanti ^[2] ; Parisa,Rashidi ^[4] ; Azra,Bihorac ^[2]

作者单位： Department of Surgery, University of Florida Health, Gainesville, FL, United States.;Intelligent Critical Care Center, University of Florida, Gainesville, FL, United States. ^[1] Intelligent Critical Care Center, University of Florida, Gainesville, FL, United States.;Department of Medicine, University of Florida, Gainesville, FL, United States. ^[2] Department of Surgery, University of Florida Health, Gainesville, FL, United States. ^[3] Intelligent Critical Care Center, University of Florida, Gainesville, FL, United States.;Department of Biomedical Engineering, University of Florida, Gainesville, FL, United States. ^[4]

关键词 FHIR Fast Healthcare Interoperability Resources clinical decision support system clinical informatics decision support information systems interoperability interoperable machine learning ontologies ontology review methodology review methods scoping review

DOI 10.2196/48297

PMID 37646309

发布时间 2025-07-22

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