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Updated: Apr 16, 2026

A Data-Driven Approach to Quantifying Immune States in Sepsis
07:42

A Data-Driven Approach to Quantifying Immune States in Sepsis

Published on: February 7, 2025

591

Interpretable machine learning for early prediction of sepsis-induced coagulopathy: a multicenter retrospective

Qingyun Peng1, Yanzi Guo1, Haoyuan Tang1

  • 1Jiangsu Provincial Key Laboratory of Critical Care Medicine, Department of Critical Care Medicine, School of Medicine, Zhongda Hospital, Southeast University, No. 87, Dingjiaqiao Road, Gulou District, Nanjing, 210009, People's Republic of China.

BMC Medical Informatics and Decision Making
|April 14, 2026
PubMed
Abstract

No abstract available in PubMed .

Keywords:
Early predictionMachine learningSHAP interpretabilitySepsis induced coagulopathyXGBoost model

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