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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Hlavní autoři:	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
Médium:	Artigo
Jazyk:	Inglês
Vydáno:	BMC 2026-03-01
Edice:	Journal of Translational Medicine
Témata:	Sepsis-induced coagulopathy Disseminated intravascular coagulation Machine learning Two-stage feature selection Interpretability
On-line přístup:	https://doi.org/10.1186/s12967-026-08067-4
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