Explainable AI (XAI) Model for ICU Sepsis Early Prediction
Temporal XGBoost and SHAP framework predicting patient sepsis onset 6 hours in advance from fluctuating vital sign telemetry.
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Project Technical Overview
Processes multivariate intensive care unit time-series data (heart rate, lactate levels, WBC counts). Employs SHAP (SHapley Additive exPlanations) to provide clinicians with clear feature attribution graphs detailing exactly why an alert was triggered, fostering clinical trust.
Read the foundational IEEE conference research paper, citations, and algorithmic architecture for this project.