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Clinician preferences for explainable AI in critical care: a comparative study of interpretable models and visualizations for intubation decision support
0
Zitationen
6
Autoren
2026
Jahr
Abstract
This study advances clinical XAI by introducing a time-aware explanation framework for ICU intubation decisions. By integrating temporal trends with model reasoning, our visualizations closely align with clinicians' cognitive workflows. Rigorous clinician-centered evaluation identified the dual-encoded SHAP heatmap as the most useful and workflow-compatible visualization, highlighting the importance of explanation design alongside predictive accuracy for clinical adoption.
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