Artificial Intelligence-Driven Algorithmic Frameworks for Health Security Management and Hospital Administration - Mousa, Samih Mohammed Hassan; Mansour Mayudh S. Alharthi; Ali Mohammed Ali Hamdi; Faisal Mohammed Mohammed Hazazi; Bandar Mahdi Ahmed Mobarki; Khalid Hassan Yousef Mobarki; Rahaf Hussain Ali Daghriry; Norah Saleh Fathuldeen Sumayli; Fahhad Muflih Faleh Aldawsari (Saudi Journal of Medicine and Public Health, 2025)
Background: The rapid digital transformation of healthcare has significantly improved clinical efficiency, interoperability, and patient-centered care through the widespread adoption of electronic health records, Internet of Medical Things (IoMT) devices, telemedicine, cloud computing, and artificial intelligence. However, this increased connectivity has simultaneously expanded the cybersecurity threat landscape, exposing healthcare organizations to sophisticated attacks that threaten patient privacy, data integrity, and service continuity. Blockchain technology and intelligent algorithmic approaches have emerged as promising solutions for strengthening healthcare cybersecurity while ensuring secure and transparent data management. Aim: This review aimed to examine blockchain-based and algorithm-driven health security systems, evaluate their effectiveness in mitigating major cyber threats, and identify current challenges, limitations, and future research directions for securing modern healthcare information systems. Methods: A comprehensive narrative review of recent literature was conducted, focusing on blockchain architectures, artificial intelligence, cryptographic techniques, intrusion detection systems, access control mechanisms, and cybersecurity frameworks designed for healthcare environments. The reviewed studies were analyzed according to system architecture, security performance, attack mitigation capabilities, and implementation challenges. Results: The reviewed evidence demonstrated that blockchain-based systems significantly improve data integrity, authentication, transparency, traceability, and secure information sharing. Integrated artificial intelligence and cryptographic algorithms effectively mitigated unauthorized access, ransomware, denial-of-service, man-in-the-middle, data tampering, and privacy leakage attacks. Despite these advantages, challenges related to scalability, computational overhead, latency, interoperability, and user adoption remain barriers to widespread implementation. Conclusion: Blockchain integrated with advanced algorithmic security provides a robust foundation for protecting healthcare information systems. Continued advancements in artificial intelligence, scalable blockchain architectures, and adaptive cybersecurity strategies will be essential for developing resilient, secure, and trustworthy digital healthcare ecosystems.