Cross-algorithm machine learning and consensus features for early disseminated intravascular coagulation risk prediction in sepsis-induced coagulopathy

Abstract Background Sepsis-induced coagulopathy (SIC) represents an early and potentially reversible stage of coagulation dysfunction in sepsis, whereas progression to disseminated intravascular coagulation (DIC) is associated with multi-organ failure and markedly increased mortality. Although exist...

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Detalhes bibliográficos

Principais autores:	Fanxuan Chen, Xuewen Mei, Dongren Yang, Darong Hai, Xueying Bao, Hao Chen, Ruoyun Wang, Zefei Mo, Yu Xia, Li Zeng, Ziyang Zhang, Yan Zu, Qi Zhao, Jingye Pan, Xiaowei Xu
Formato:	Artigo
Idioma:	Inglês
Publicado em:	BMC 2026-03-01
Colecção:	Journal of Translational Medicine
Assuntos:	Sepsis-induced coagulopathy Disseminated intravascular coagulation Machine learning Two-stage feature selection Interpretability
Acesso em linha:	https://doi.org/10.1186/s12967-026-08067-4
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