An End-to-End Enterprise Architecture for CNN-Based Healthcare AI in Secure Cloud Environments
Abstract
The integration of Convolutional Neural Networks (CNNs) into healthcare systems has significantly advanced medical image analysis, disease diagnosis, and clinical decision support. However, deploying CNN-based healthcare AI at enterprise scale introduces challenges related to data security, regulatory compliance, interoperability, scalability, and system governance. This paper proposes an end-to-end enterprise architecture for CNN-based healthcare AI deployed in secure cloud environments. The architecture aligns business, application, data, and technology layers to ensure compliance with healthcare regulations such as HIPAA and GDPR while supporting high-performance AI workloads. The proposed framework incorporates secure data ingestion, cloud-native AI pipelines, model lifecycle management, and zero-trust security principles. Emphasis is placed on integrating CNN models into existing hospital information systems, enabling real-time and batch inference, and maintaining explainability and auditability. The architecture supports hybrid and multi-cloud deployments, ensuring resilience, scalability, and cost efficiency. By combining enterprise architecture principles with modern cloud security and AI governance practices, this work provides a practical blueprint for healthcare organizations seeking to operationalize CNN-based AI safely and effectively. The proposed approach bridges the gap between experimental AI models and production-grade healthcare systems, enabling trustworthy, scalable, and compliant AI-driven clinical solutions
Article Information
Journal |
International Journal of Science, Research and Technology |
|---|---|
Volume (Issue) |
Vol. 8 No. 6 (2025): International Journal of Science, Research and Technology (IJSRAT) |
DOI |
|
Pages |
15285-15292 |
Published |
December 5, 2025 |
| Copyright |
All rights reserved |
Open Access |
This work is licensed under a Creative Commons Attribution 4.0 International License. |
How to Cite |
Chloé Anne Rousseau (%2025). An End-to-End Enterprise Architecture for CNN-Based Healthcare AI in Secure Cloud Environments. International Journal of Science, Research and Technology , Vol. 8 No. 6 (2025): International Journal of Science, Research and Technology (IJSRAT) , pp. 15285-15292. https://doi.org/10.15662/IJSRAT.2025.0806002 |
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