Machine Learning Analysis of Time-Dependent Features for Predicting Adverse Events During Hemodialysis Therapy: Model Development and Validation Study.

Liu, Yi-Shiuan; Yang, Chih-Yu; Chiu, Ping-Fang; Lin, Hui-Chu; Lo, Chung-Chuan; Lai, Alan Szu-Han; Chang, Chia-Chu; Lee, Oscar Kuang-Sheng

Liu, Yi-Shiuan; Yang, Chih-Yu; Chiu, Ping-Fang; Lin, Hui-Chu; Lo, Chung-Chuan; Lai, Alan Szu-Han; Chang, Chia-Chu; Lee, Oscar Kuang-Sheng.

Afiliação

Liu YS; Institute of Clinical Medicine, National Yang Ming Chiao Tung University School of Medicine, Taipei, Taiwan.
Yang CY; Stem Cell Research Center, National Yang Ming Chiao Tung University, Taipei, Taiwan.
Chiu PF; Department of Physiology and Pharmacology, Chang Gung University College of Medicine, Taoyuan, Taiwan.
Lin HC; Department of Plastic and Reconstructive Surgery, Chang Gung Memorial Hospital, Taoyuan, Taiwan.
Lo CC; Institute of Clinical Medicine, National Yang Ming Chiao Tung University School of Medicine, Taipei, Taiwan.
Lai AS; Stem Cell Research Center, National Yang Ming Chiao Tung University, Taipei, Taiwan.
Chang CC; Division of Nephrology, Department of Medicine, Taipei Veterans General Hospital, Taipei, Taiwan.
Lee OK; Center for Intelligent Drug Systems and Smart Bio-devices, Hsinchu, Taiwan.

J Med Internet Res ; 23(9): e27098, 2021 09 07.

Article em En | MEDLINE | ID: mdl-34491204

Assuntos

Hipotensão; Algoritmos; Humanos; Aprendizado de Máquina; Diálise Renal

Palavras-chave

hemodialysis; intradialytic adverse events; machine learning; prediction algorithm

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Hipotensão Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Revista: J Med Internet Res Assunto da revista: INFORMATICA MEDICA Ano de publicação: 2021 Tipo de documento: Article País de afiliação: Taiwan

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