PerCaM-Health learns evolving personalized dynamic causal graphs from longitudinal health data to enable more reliable patient-level counterfactual queries than cohort or per-patient baselines.
CDF-RAG: Causal dynamic feedback for adaptive retrieval-augmented generation
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CARE-ECG unifies ECG representation learning, causal graph-based diagnosis, and counterfactual assessment in an agentic LLM pipeline to improve accuracy and explanation faithfulness.
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PerCaM-Health: Personalized Dynamic Causal Graphs for Healthcare Reasoning
PerCaM-Health learns evolving personalized dynamic causal graphs from longitudinal health data to enable more reliable patient-level counterfactual queries than cohort or per-patient baselines.
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CARE-ECG: Causal Agent-based Reasoning for Explainable and Counterfactual ECG Interpretation
CARE-ECG unifies ECG representation learning, causal graph-based diagnosis, and counterfactual assessment in an agentic LLM pipeline to improve accuracy and explanation faithfulness.