Mr. Sushil Prabhu Prabhakaran

Cloud-Enabled AI Infrastructure in Healthcare: A Systematic Review of Clinical Decision Support and Workflow Optimization

Abstract:

This article examines the integration of Cloud Intelligence and AIOps (Artificial Intelligence for IT Operations) in modern cloud engineering environments, focusing on converging AI-driven decision systems and workflow orchestration. The article analyzes how this integration enhances operational efficiency, system resilience, and cost optimization in cloud infrastructures while maintaining robust security and compliance standards. This article comprehensively examines automated resource management, predictive analytics, and self-healing capabilities, demonstrating how Cloud Intelligence transforms traditional IT operations into autonomous, adaptive systems. The findings reveal that implementing AIOps significantly improves incident response times, reduces manual intervention, and enables proactive maintenance through advanced anomaly detection and federated learning approaches. Furthermore, the article highlights the critical role of real-time data integration and dynamic workflow orchestration in achieving optimal cloud performance and reliability. This article contributes to the growing knowledge in cloud engineering by providing a structured framework for implementing Cloud Intelligence solutions. It offers insights into the future evolution of AI-driven cloud operations.