Risk stratification and data-driven phenotyping of peripherally inserted central catheter-related bloodstream infection: an explainable machine learning analysis of a large critical care cohort

Abstract Background Peripherally inserted central catheter-related bloodstream infections (PICC-CRBSIs) are significant causes of morbidity and mortality in critically ill patients. Therefore, improved risk stratification is required for targeted prevention. This study aimed to identify key predicto...

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Autors principals:	Yujia Liu, Chao Cong, Dongsheng Cheng
Format:	Artigo
Idioma:	Inglês
Publicat:	BMC 2026-03-01
Col·lecció:	BMC Medical Informatics and Decision Making
Matèries:	Machine learning Peripherally Inserted Central Catheter (PICC) Catheter-related bloodstream infection (CRBSI) Explainable artificial intelligence (XAI) Critical care
Accés en línia:	https://doi.org/10.1186/s12911-026-03419-y
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