Detection of Bacteremia in Surgical In-Patients Using Recurrent Neural Network Based on Time Series Records: Development and Validation Study.

Park, Hyung Jun; Jung, Dae Yon; Ji, Wonjun; Choi, Chang-Min

Park, Hyung Jun; Jung, Dae Yon; Ji, Wonjun; Choi, Chang-Min.

Afiliação

Park HJ; Department of Pulmonary and Critical Care Medicine, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea.
Jung DY; Big Data & AI Lab, Hana Institute of Technology, Hana TI, Seoul, Republic of Korea.
Ji W; Department of Pulmonary and Critical Care Medicine, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea.
Choi CM; Department of Pulmonary and Critical Care Medicine, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea.

J Med Internet Res ; 22(8): e19512, 2020 08 04.

Article em En | MEDLINE | ID: mdl-32669261

Assuntos

Bacteriemia/diagnóstico; Aprendizado Profundo/normas; Redes Neurais de Computação; Feminino; Humanos; Pacientes Internados; Masculino; Estudos Retrospectivos

Palavras-chave

bacteremia; deep learning; early detection; informatics; modeling; neural network; recurrent neural network; sepsis; surgery; time series

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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Redes Neurais de Computação / Bacteriemia / Aprendizado Profundo Tipo de estudo: Diagnostic_studies / Observational_studies / Prognostic_studies / Risk_factors_studies / Screening_studies Limite: Female / Humans / Male Idioma: En Revista: J Med Internet Res Assunto da revista: INFORMATICA MEDICA Ano de publicação: 2020 Tipo de documento: Article

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