A Secure and Real-Time AWS Cloud Framework for AI-Based Medical Image Analysis with SAP Connectivity

Abstract

The rapid growth of medical imaging data has created a critical need for scalable, secure, and real-time analytical frameworks capable of supporting advanced artificial intelligence (AI) applications in clinical environments. This work presents a secure and real-time AWS cloud–based framework for AI-driven medical image analysis with integrated SAP connectivity, designed to enable efficient image processing, model inference, and enterprise system integration. The proposed architecture leverages deep learning models for automated image analysis while utilizing AWS-native services to support real-time data ingestion, processing, and scalable deployment. Secure data pipelines are implemented to ensure confidentiality, integrity, and compliance with healthcare data protection requirements, while SAP integration enables seamless interoperability with hospital information systems and enterprise workflows. Real-time processing capabilities support low-latency clinical decision-making, and the cloud-native design allows elastic scaling to accommodate growing imaging workloads. This framework demonstrates how combining deep learning, cloud infrastructure, real-time data pipelines, and secure enterprise integration can enhance the reliability, efficiency, and clinical applicability of AI-based medical image analysis systems.