Article

Deep Temporal-Sepsis: A Calibrated Transformer Framework for Early ICU Sepsis Prediction with Grad-CAM Temporal Phenotyping

2026-06-12

Abstract excerpt

<h4>Background: </h4> /Objectives: Sepsis is responsible for approximately 270,000 deaths annually in the United States. Conventional scoring systems, such as SOFA and qSOFA, are largely reactive and do not effectively leverage longitudinal ICU data for early prediction. This study aimed to develop a deep learning framework capable of predicting sepsis onset up to 6 hours before Sepsis-3 criteria are met, while al...

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Literature Corpus work: e2069bd2-f52e-5150-974e-018b3c0566d9
DOI: 10.20944/preprints202606.1033.v1

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