Advancing Healthcare Security and Insights: A Review of AI-Driven Cybersecurity, Machine Learning, and Data Analytics

Abstract

Artificial Intelligence (AI), Machine Learning (ML), and data analytics are changing healthcare, making it more diagnostic, personalized, and more efficient, and enhancing cybersecurity. ML can be used to predict potential threats and monitor abnormalities in real-time, whereas data analytics can be used to draw actionable inferences regarding large volumes of clinical and operational data. Combining these technologies enhances the security of patient data, regulatory adherence, and decision-making, which make up a proactive and smart healthcare ecosystem. Nevertheless, as solutions to the problem of data privacy, algorithmic bias, and interoperability, the new trends, like the use of precision medicine, explainable AI, and collaborative AI systems, can bring safer, more efficient and equitable healthcare. This review identifies their present uses, issues, and perspectives.