AI in Securing Electronic Health Records (EHR) Systems

Abstract

The rapid digital transformation in healthcare has led to an increased reliance on Electronic Health Records (EHR) systems, making them prime targets for cyber threats. This paper explores the application of Artificial Intelligence (AI) in enhancing the security of EHR systems, focusing on methods to ensure the confidentiality and integrity of sensitive patient information. We analyze various AI-driven techniques, including machine learning algorithms for anomaly detection, natural language processing for risk assessment, and predictive analytics for threat forecasting. Additionally, we examine the role of AI in automating security protocols, improving user authentication processes, and facilitating real-time monitoring of EHR systems. By integrating AI into EHR security frameworks, healthcare organizations can better protect against unauthorized access, data breaches, and compliance failures, ultimately fostering patient trust and safeguarding critical health data.