Secure Cloud Architecture for Clinical Decision Support Using Oracle Autonomous AI Pipelines and SAP-Enabled Data Integration
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Abstract
The growing complexity of healthcare data and the demand for real-time clinical insights necessitate intelligent, scalable, and secure digital infrastructures. This study presents a secure cloud architecture for clinical decision support that integrates Oracle Autonomous AI pipelines with SAP-enabled data management. The proposed framework leverages Oracle Cloud Infrastructure (OCI), Oracle Machine Learning (OML), and Autonomous Data Warehouse (ADW) to automate data ingestion, preprocessing, model training, and inference for clinical risk prediction and diagnostic support. SAP integration ensures seamless interoperability with hospital information systems, enabling efficient workflow management and unified access to patient records, laboratory data, and operational metrics. A multilayer security model incorporating identity governance, encryption, firewall intelligence, and continuous auditing safeguards sensitive clinical information across the architecture. The combined system enhances clinical decision-making through accurate AI-driven predictions, strengthens data integrity, and supports a resilient, scalable cloud environment suitable for modern healthcare institutions.
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