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Identifying key genes related to inflammasome in severe COVID-19 patients based on a joint model with random forest and artificial neural network.
Ou, Haiya; Fan, Yaohua; Guo, Xiaoxuan; Lao, Zizhao; Zhu, Meiling; Li, Geng; Zhao, Lijun.
  • Ou H; Department of Gastroenterology, Shenzhen Bao'an Traditional Chinese Medicine Hospital, Guangzhou University of Chinese Medicine, Shenzhen, China.
  • Fan Y; Traditional Chinese Medicine Innovation Research Center, Shenzhen Hospital of Integrated Traditional Chinese and Western Medicine, Shenzhen, China.
  • Guo X; Laboratory Animal Center, Guangzhou University of Chinese Medicine, Guangzhou, China.
  • Lao Z; Traditional Chinese Medicine Innovation Research Center, Shenzhen Hospital of Integrated Traditional Chinese and Western Medicine, Shenzhen, China.
  • Zhu M; Laboratory Animal Center, Guangzhou University of Chinese Medicine, Guangzhou, China.
  • Li G; Traditional Chinese Medicine Innovation Research Center, Shenzhen Hospital of Integrated Traditional Chinese and Western Medicine, Shenzhen, China.
  • Zhao L; Laboratory Animal Center, Guangzhou University of Chinese Medicine, Guangzhou, China.
Front Cell Infect Microbiol ; 13: 1139998, 2023.
Article en En | MEDLINE | ID: mdl-37113134
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Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Inflamasomas / COVID-19 Tipo de estudio: Clinical_trials / Systematic_reviews Límite: Humans Idioma: En Año: 2023 Tipo del documento: Article
Texto completo
Imprimir
XML
PubMed Links
Search on Google

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Inflamasomas / COVID-19 Tipo de estudio: Clinical_trials / Systematic_reviews Límite: Humans Idioma: En Año: 2023 Tipo del documento: Article