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Performance of a Machine Learning Algorithm Using Electronic Health Record Data to Predict Postoperative Complications and Report on a Mobile Platform.
Ren, Yuanfang; Loftus, Tyler J; Datta, Shounak; Ruppert, Matthew M; Guan, Ziyuan; Miao, Shunshun; Shickel, Benjamin; Feng, Zheng; Giordano, Chris; Upchurch, Gilbert R; Rashidi, Parisa; Ozrazgat-Baslanti, Tezcan; Bihorac, Azra.
Afiliación
  • Ren Y; Intelligent Critical Care Center, University of Florida, Gainesville.
  • Loftus TJ; Division of Nephrology, Hypertension, and Renal Transplantation, Department of Medicine, University of Florida, Gainesville.
  • Datta S; Intelligent Critical Care Center, University of Florida, Gainesville.
  • Ruppert MM; Department of Surgery, University of Florida, Gainesville.
  • Guan Z; Intelligent Critical Care Center, University of Florida, Gainesville.
  • Miao S; Division of Nephrology, Hypertension, and Renal Transplantation, Department of Medicine, University of Florida, Gainesville.
  • Shickel B; Intelligent Critical Care Center, University of Florida, Gainesville.
  • Feng Z; Division of Nephrology, Hypertension, and Renal Transplantation, Department of Medicine, University of Florida, Gainesville.
  • Giordano C; Intelligent Critical Care Center, University of Florida, Gainesville.
  • Upchurch GR; Division of Nephrology, Hypertension, and Renal Transplantation, Department of Medicine, University of Florida, Gainesville.
  • Rashidi P; Intelligent Critical Care Center, University of Florida, Gainesville.
  • Ozrazgat-Baslanti T; Division of Nephrology, Hypertension, and Renal Transplantation, Department of Medicine, University of Florida, Gainesville.
  • Bihorac A; Intelligent Critical Care Center, University of Florida, Gainesville.
JAMA Netw Open ; 5(5): e2211973, 2022 05 02.
Article en En | MEDLINE | ID: mdl-35576007
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Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Inteligencia Artificial / Registros Electrónicos de Salud Tipo de estudio: Etiology_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Límite: Adult / Female / Humans / Male / Middle aged Idioma: En Revista: JAMA Netw Open Año: 2022 Tipo del documento: Article
Texto completo
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PubMed Links
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Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Inteligencia Artificial / Registros Electrónicos de Salud Tipo de estudio: Etiology_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Límite: Adult / Female / Humans / Male / Middle aged Idioma: En Revista: JAMA Netw Open Año: 2022 Tipo del documento: Article