Construction and external validation of a 5-gene random forest model to diagnose non-obstructive azoospermia based on the single-cell RNA sequencing of testicular tissue.

Zhou, Ranran; Lv, Xianyuan; Chen, Tianle; Chen, Qi; Tian, Hu; Yang, Cheng; Guo, Wenbin; Liu, Cundong

Zhou, Ranran; Lv, Xianyuan; Chen, Tianle; Chen, Qi; Tian, Hu; Yang, Cheng; Guo, Wenbin; Liu, Cundong.

Afiliação

Zhou R; Department of Urology, The Third Affiliated Hospital of Southern Medical University, Guangzhou, China.
Lv X; The Third School of Clinical Medicine, Southern Medical University, Guangzhou, China.
Chen T; Department of Urology, The Third Affiliated Hospital of Southern Medical University, Guangzhou, China.
Chen Q; The Third School of Clinical Medicine, Southern Medical University, Guangzhou, China.
Tian H; Department of Urology, The Third Affiliated Hospital of Southern Medical University, Guangzhou, China.
Yang C; The Third School of Clinical Medicine, Southern Medical University, Guangzhou, China.
Guo W; Department of Urology, The Third Affiliated Hospital of Southern Medical University, Guangzhou, China.
Liu C; The Third School of Clinical Medicine, Southern Medical University, Guangzhou, China.

Aging (Albany NY) ; 13(21): 24219-24235, 2021 11 04.

Article em En | MEDLINE | ID: mdl-34738918

Assuntos

Azoospermia/diagnóstico; Azoospermia/genética; Aprendizado de Máquina; RNA-Seq/métodos; Análise de Célula Única/métodos; Adulto; Diagnóstico por Computador; Humanos; Masculino; Mapas de Interação de Proteínas/genética; Transcriptoma/genética

Palavras-chave

diagnosis; machine learning; non-obstructive azoospermia; random forest; scRNA-seq

Texto completo

Imprimir

XML

PubMed Links

Buscar no Google

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Azoospermia / Análise de Célula Única / Aprendizado de Máquina / RNA-Seq Idioma: En Ano de publicação: 2021 Tipo de documento: Article

Texto completo

Imprimir

XML

PubMed Links

Buscar no Google