Navigating Data Privacy, Security, and Regulatory Challenges in Healthcare AI Ensuring Fairness, Bias Mitigation, Interpretability, and Trust

Transformers in healthcare are revolutionizing medical applications by enhancing EHR processing, drug discovery, medical imaging, and clinical decision support. This study reviews their technical foundations, robust data processing, and predictive capabilities. It explores key challenges, including data privacy, security, regulations, and bias, while emphasizing responsible AI use. Future directions include multimodal data integration, federated learning, and lightweight models for optimized healthcare solutions.

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