Article

Explainable AI-driven heterogeneity using coagulation–inflammatory markers improves prognosis prediction, risk stratification, and anticoagulant treatment effects for sepsis

2025-02-27

Abstract excerpt

<title>Abstract</title> <p>Sepsis, a leading cause of hospital mortality, is characterized by substantial heterogeneity, hindering the development of effective and interpretable prognostic and stratification methods. To address this challenge, we developed an explainable prognostic model (SepsisFormer, a transformer-based deep neural network with an enhanced domain-adaptive generator) and an automated risk strati...

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Literature Corpus work: c6833ee6-45af-57eb-9702-f71fce202624
DOI: 10.21203/rs.3.rs-5835917/v1

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