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boumezbeuraya / SecureMed-LLM-A-Privacy-Preserving1-Framework-for-Safeguarding-Clinical2-Language-Models

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SecureMed-LLM: A privacy-preserving framework for clinical report generation from chest X-rays, integrating Med-Guard anonymization, DP-SGD (ε=3.0), adversarial training, IDS-LLM validation, and ECIES/Curve25519 encryption. PeerJ Computer Science 2025.

natural-language-processing deep-learning transformers pytorch ecies differential-privacy chest-xray federated-learning clinical-nlp privacy-preserving-ml medical-ai adversarial-robustness healthcare-ai membership-inference opacus radiology-report-generation llm-security biomedclip phi-deidentification open-i
  • Updated Jun 18, 2026
  • Python

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