A timestamp-attributed event graph with bidirectional edges predicts ICU mortality at AUROC 0.8449, but the paper's ablations show heterogeneous edge typing did not help and its flagship 'bidirectional necessity' claim conflicts with its own edge definitions.
MIMIC-IF: Interpretability and Fairness Evaluation of Deep Learning Models on MIMIC-IV,
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CT-HEG: A Bidirectional, Timestamp-Attributed Event Graph for ICU In-Hospital Mortality Prediction - An Architectural Ablation Study
A timestamp-attributed event graph with bidirectional edges predicts ICU mortality at AUROC 0.8449, but the paper's ablations show heterogeneous edge typing did not help and its flagship 'bidirectional necessity' claim conflicts with its own edge definitions.