Diagnostic potential of a gradient boosting-based model for detecting pediatric sepsis.

Ying, Jianchao; Wang, Qian; Xu, Teng; Lu, Zhongqiu

Ying, Jianchao; Wang, Qian; Xu, Teng; Lu, Zhongqiu.

Afiliação

Ying J; Central Laboratory, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China; Institute of Emergency Medicine, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China. Electronic address: yingjc@wmu.edu.cn.
Wang Q; Department of Clinical Laboratory, Wenzhou People's Hospital, The Third Clinical Institute Affiliated to Wenzhou Medical University, Wenzhou, China.
Xu T; Institute of Translational Medicine, Baotou Central Hospital, Baotou, China.
Lu Z; Institute of Emergency Medicine, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China; Emergency Department, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China. Electronic address: lzq640815@163.com.

Genomics ; 113(1 Pt 2): 874-883, 2021 01.

Article em En | MEDLINE | ID: mdl-33096256

Assuntos

Sepse/genética; Transcriptoma; Biomarcadores/metabolismo; Criança; Biologia Computacional/métodos; Humanos; Aprendizado de Máquina; Prognóstico; Sepse/metabolismo; Sepse/patologia

Palavras-chave

Diagnostic model; Gene marker; Genome-wide expression profiles; Machine learning; Pediatric sepsis

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Sepse / Transcriptoma Tipo de estudo: Diagnostic_studies / Prognostic_studies Limite: Child / Humans Idioma: En Ano de publicação: 2021 Tipo de documento: Article

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