13 papers
Membership Inference Attacks Expose Participation Privacy in ECG Foundation Encoders
Ziyu Wang, Elahe Khatibi, Ankita Sharma +4
Foundation-style ECG encoders pretrained with self-supervised learning are increasingly reused across tasks, institutions, and deployment contexts, often through model-as-a-service…
CARE-ECG: Causal Agent-based Reasoning for Explainable and Counterfactual ECG Interpretation
Elahe Khatibi, Ziyu Wang, Ankita Sharma +4
Large language models (LLMs) enable waveform-to-text ECG interpretation and interactive clinical questioning, yet most ECG-LLM systems still rely on weak signal-text alignment and…
FairTabGen: High-Fidelity and Fair Synthetic Health Data Generation from Limited Samples
Nitish Nagesh, Salar Shakibhamedan, Mahdi Bagheri +4
Synthetic healthcare data generation offers a promising solution to research limitations in clinical settings caused by privacy and regulatory constraints. However, current synthet…
Linkage Attacks Expose Identity Risks in Public ECG Data Sharing
Ziyu Wang, Elahe Khatibi, Farshad Firouzi +3
The increasing availability of publicly shared electrocardiogram (ECG) data raises critical privacy concerns, as its biometric properties make individuals vulnerable to linkage att…
MedCoT-RAG: Causal Chain-of-Thought RAG for Medical Question Answering
Ziyu Wang, Elahe Khatibi, Amir M. Rahmani
Large language models (LLMs) have shown promise in medical question answering but often struggle with hallucinations and shallow reasoning, particularly in tasks requiring nuanced…
FairCauseSyn: Towards Causally Fair LLM-Augmented Synthetic Data Generation
Nitish Nagesh, Ziyu Wang, Amir M. Rahmani
Synthetic data generation creates data based on real-world data using generative models. In health applications, generating high-quality data while maintaining fairness for sensiti…