Understanding the risk factors for adverse events during exchange transfusion in neonatal hyperbilirubinemia using explainable artificial intelligence.

Zhu, Shuzhen; Zhou, Lianjuan; Feng, Yuqing; Zhu, Jihua; Shu, Qiang; Li, Haomin

Zhu, Shuzhen; Zhou, Lianjuan; Feng, Yuqing; Zhu, Jihua; Shu, Qiang; Li, Haomin.

Afiliação

Zhu S; The Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou, China.
Zhou L; The Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou, China.
Feng Y; The Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou, China.
Zhu J; The Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou, China.
Shu Q; The Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou, China.
Li H; The Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou, China. hmli@zju.edu.cn.

BMC Pediatr ; 22(1): 567, 2022 09 30.

Article em En | MEDLINE | ID: mdl-36180854

Assuntos

Inteligência Artificial; Hiperbilirrubinemia Neonatal; Criança; Transfusão Total/efeitos adversos; Humanos; Hiperbilirrubinemia Neonatal/etiologia; Hiperbilirrubinemia Neonatal/terapia; Lactente; Recém-Nascido; Estudos Retrospectivos; Fatores de Risco

Palavras-chave

Adverse events; Exchange transfusion; Explainable artificial intelligence; Risk factors

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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Inteligência Artificial / Hiperbilirrubinemia Neonatal Idioma: En Ano de publicação: 2022 Tipo de documento: Article

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