An Interpretable Early Dynamic Sequential Predictor for Sepsis-Induced Coagulopathy Progression in the Real-World Using Machine Learning

Sepsis-associated coagulation dysfunction greatly increases the mortality of sepsis. Irregular clinical time-series data remains a major challenge for AI medical applications. To early detect and manage sepsis-induced coagulopathy (SIC) and sepsis-associated disseminated intravascular coagulation (D...

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Detalles Bibliográficos
Autores principales: Cui, Ruixia, Hua, Wenbo, Qu, Kai, Yang, Heran, Tong, Yingmu, Li, Qinglin, Wang, Hai, Ma, Yanfen, Liu, Sinan, Lin, Ting, Zhang, Jingyao, Sun, Jian, Liu, Chang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Medicine
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8678506/
https://www.ncbi.nlm.nih.gov/pubmed/34926518
http://dx.doi.org/10.3389/fmed.2021.775047

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8678506/
https://www.ncbi.nlm.nih.gov/pubmed/34926518
http://dx.doi.org/10.3389/fmed.2021.775047

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