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Hasan+and+Ahmed Rastv4i3253567 by abdulmuminbraimah is a document available to read on EtoBox.

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The study investigates the use of AI-driven anomaly detection to enhance data loss prevention and security assurance in electronic health records (EHRs). It systematically analyzes 96 peer-reviewed studies, revealing that machine learning algorithms significantly improve detection accuracy and reduce unauthorized data transfers. The findings highlight the potential of AI to transform traditional security measures into dynamic, evidence-based systems that ensure patient data protection and regulatory complia

Author

abdulmuminbraimah

Language

EN