Healthcare Informatics and Cybersecurity: A Review of AI and Machine Learning for Predictive Analytics, Data Analytics, and Supply Chain Systems

Abstract

The high pace of digitalization in the sphere of healthcare resulted in the emergence of large volumes of multifaceted information, which requires sophisticated methods of computation to enhance patient care, efficiency, and system safety. This paper examines the use of Artificial Intelligence (AI) and Machine Learning (ML) in healthcare informatics, predictive analytics, data analytics, and cybersecurity and supply chain management. Models based on AI can be used to predict diseases in advance, plan treatment by case, and optimize the management of hospital resources. Also, AI and ML can be used to improve cybersecurity by identifying and preventing any threats to sensitive patient information. The problems of data quality, integration, ethical issues and compliance are outlined and future research prospects linked to develop secure, efficient, intelligent healthcare systems are discussed. This paper demonstrates that AI-based solutions have the potential to transform healthcare practices to create resilient, data-driven, and patient-centered healthcare settings.