Transforming Healthcare Intelligence and Risk Detection through AI-Driven Analytics on Oracle Cloud Infrastructure

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Authors: M. Sunil kumar
Cited by: 0
References: 2

Abstract

The integration of artificial intelligence with cloud computing is transforming the healthcare industry by enabling advanced data-driven insights and proactive risk management. This study explores how AI-driven analytics on Oracle Cloud Infrastructure can enhance healthcare intelligence and improve early risk detection in clinical and operational environments. Modern healthcare systems generate vast volumes of structured and unstructured data from electronic health records, medical imaging, wearable devices, and hospital information systems. Leveraging scalable cloud services and machine learning capabilities, healthcare organizations can process these large datasets in real time to identify patterns, predict potential health risks, and support clinical decision-making. The proposed framework utilizes cloud-based data integration, storage, and AI analytics tools to enable predictive modeling, anomaly detection, and real-time business intelligence. By analyzing patient data continuously, the system can help detect disease risks, monitor patient health trends, and optimize hospital operations while maintaining high levels of data security and compliance. Furthermore, the adoption of AI-powered analytics on cloud platforms allows healthcare providers to improve patient outcomes, reduce operational costs, and enhance preventive care strategies. This approach demonstrates how intelligent cloud infrastructure combined with advanced analytics can support a more responsive, efficient, and data-driven healthcare ecosystem capable of addressing emerging medical and operational challenges

Fields of Study & Subjects

Internet of Things and AI Artificial Intelligence in Healthcare Artificial Intelligence in Healthcare and Education

Publication details

Journal / source
International Journal of Science Research and Technology
Volume
09
Issue
01
Publication date
18 January 2026
Language
EN