Healthcare Transformation through AI, Machine Learning, Cybersecurity, Analytics, and Supply Chains

Abstract

The development of Artificial Intelligence (AI), Machine Learning (ML), data analytics, cybersecurity, and intelligent supply chains systems is proceeding at a rapid pace and transforms the entire modern healthcare in a holistic manner. In this review, we have examined how these technologies have been integrated to improve clinical decision-making, operational efficiency, data security, and resilience of supply ns. It also aids in predictive diagnostics, personalized medicine and clinical decision support with the help of AI and ML applications, making interventions timely and more accurate. Data analytics allows drawing actionable insights using big and complex data on health care, supporting real-time monitoring, population health management, and strategic planning. Other challenges in integration identified in the review are interoperability barriers, data quality, and biases in algorithms, privacy protection, and the adaptation of the workforce. The future of intelligent healthcare ecosystems is determined by the emerging trends like federated learning, explainable AI, edge computing, and autonomous supply networks. In general, the integration of these technologies provides a route to safe, evidence-based, effective, and patient-centered healthcare systems.