Healthcare Focused AI Cloud Architecture Enabling Governance Risk Oversight and Digital Trust via Machine Learning
Abstract
The rapid digital transformation of healthcare systems has intensified the need for robust governance, effective risk oversight, and sustained digital trust. Traditional healthcare IT infrastructures struggle to manage increasing data volumes, regulatory complexity, and evolving cyber threats. This study proposes a healthcare-focused artificial intelligence (AI) cloud architecture that leverages machine learning to enhance governance automation, predictive risk management, and trust-centric digital operations. The architecture integrates cloud-native scalability, intelligent analytics, and policy-driven controls to support continuous compliance, real-time risk detection, and privacy-preserving data governance. Machine learning models are employed to monitor system behavior, enforce access policies, classify data sensitivity, and predict operational and security risks. The proposed approach addresses key challenges in healthcare, including regulatory adherence, interoperability, data privacy, and system resilience. Through architectural analysis and methodological validation, the study demonstrates how AI-enabled cloud systems can transform governance from static oversight to adaptive, intelligence-driven processes. The findings highlight the potential of scalable AI cloud architectures to improve transparency, accountability, and trust across healthcare digital ecosystems while supporting innovation and sustainable digital transformation.
Article Information
Journal |
International Journal of Science, Research and Technology |
|---|---|
Volume (Issue) |
Vol. 7 No. 5 (2024): International Journal of Science, Research and Technology (IJSRAT) |
DOI |
|
Pages |
12779-12785 |
Published |
September 5, 2024 |
| Copyright |
All rights reserved |
Open Access |
This work is licensed under a Creative Commons Attribution 4.0 International License. |
How to Cite |
Sofia Elin Karlsson (%2024). Healthcare Focused AI Cloud Architecture Enabling Governance Risk Oversight and Digital Trust via Machine Learning. International Journal of Science, Research and Technology , Vol. 7 No. 5 (2024): International Journal of Science, Research and Technology (IJSRAT) , pp. 12779-12785. https://doi.org/10.15662/IJSRAT.2024.0705002 |
References
2. Sudhan, S. K. H. H., & Kumar, S. S. (2016). Gallant Use of Cloud by a Novel Framework of Encrypted Biometric Authentication and Multi Level Data Protection. Indian Journal of Science and Technology, 9, 44.
3. Gopinathan, V. R. (2024). AI-Driven Customer Support Automation: A Hybrid Human–Machine Collaboration Model for Real-Time Service Delivery. International Journal of Technology, Management and Humanities, 10(01), 67-83.
4. Kesavan, E. (2023). ML-Based Detection of Credit Card Fraud Using Synthetic Minority Oversampling. International Journal of Innovations in Science, Engineering And Management, 55-62.
5. Ramidi, M. (2022). Developing resilient offline-first architectures for mobile health and clinical research applications. International Journal of Computer Technology and Electronics Communication (IJCTEC), 5(1), 4518–4529.
6. Gangina, P. (2023). Edge computing architectures for IoT data aggregation in industrial manufacturing. International Journal of Humanities and Information Technology (IJHIT), 5(1), 48–67. https://www.ijhit.info
7. Anand, L., & Neelanarayanan, V. (2019). Liver disease classification using deep learning algorithm. BEIESP, 8(12), 5105–5111.
8. Natta, P. K. (2023). Harmonizing enterprise architecture and automation: A systemic integration blueprint. International Journal of Research Publications in Engineering, Technology and Management (IJRPETM), 6(6), 9746–9759. https://doi.org/10.15662/IJRPETM.2023.0606016
9. Navandar, P. (2022). The Evolution from Physical Protection to Cyber Defense. International Journal of Computer Technology and Electronics Communication, 5(5), 5730-5752.
10. Zerine, I., Islam, M. S., Ahmad, M. Y., Islam, M. M., & Biswas, Y. A. (2023). AI-Driven Supply Chain Resilience: Integrating Reinforcement Learning and Predictive Analytics for Proactive Disruption Management. Business and Social Sciences, 1(1), 1-12.
11. Jayaraman, S., Rajendran, S., & P, S. P. (2019). Fuzzy c-means clustering and elliptic curve cryptography using privacy preserving in cloud. International Journal of Business Intelligence and Data Mining, 15(3), 273-287.
12. Genne, S. (2023). Optimizing user experience in high-traffic financial web applications using analytics. International Journal of Engineering & Extended Technologies Research (IJEETR), 5(5), 7231–7241.
13. Chivukula, V. (2024). The Role of Adstock and Saturation Curves in Marketing Mix Models: Implications for Accuracy and Decision-Making. International Journal of Advanced Research in Computer Science & Technology (IJARCST), 7(2), 10002-10007.
14. Mudunuri, P. R. (2023). Governance-aware infrastructure-as-code for regulated research environments. International Journal of Research in Engineering, Project Management and Technology (IJRPETM), 6(4), 9017–9028.
15. Rahman, M. R., Rahman, M., Rasul, I., Arif, M. H., Alim, M. A., Hossen, M. S., & Bhuiyan, T. (2024). Lightweight Machine Learning Models for Real-Time Ransomware Detection on Resource-Constrained Devices. Journal of Information Communication Technologies and Robotic Applications, 15(1), 17-23.
16. Ponugoti, M. (2023). Bridging the digital divide: Architecture for equitable technological access. International Journal of Computer Technology and Electronics Communication (IJCTEC), 6(3), 6991–7002.
17. Kusumba, S. (2023). A Unified Data Strategy and Architecture for Financial Mastery: AI, Cloud, and Business Intelligence in Healthcare. International Journal of Computer Technology and Electronics Communication, 6(3), 6974-6981.
18. Ananth, S., Radha, D. K., Prema, D. S., & Nirajan, K. (2019). Fake news detection using convolution neural network in deep learning. International Journal of Innovative Research in Computer and Communication Engineering, 7(1), 49-63.
19. Devarajan, R., Prabakaran, N., Vinod Kumar, D., Umasankar, P., Venkatesh, R., & Shyamalagowri, M. (2023, August). IoT Based Under Ground Cable Fault Detection with Cloud Storage. In 2023 Second International Conference on Augmented Intelligence and Sustainable Systems (ICAISS) (pp. 1580-1583). IEEE.
20. Sriramoju, S. (2023). Optimizing customer and order automation in enterprise systems using event-driven design. International Journal of Research Publications in Engineering, Technology and Management (IJRPETM), 6(4), 9006–9016.
21. Chinthalapelly, P. R., Panda, M. R., & Gorle, S. (2023). Digital Identity Verification Using Federated Learning. Artificial Intelligence, Machine Learning, and Autonomous Systems, 7, 40-74.
22. Keezhadath, A. A., & Amarapalli, L. (2024). Ensuring Data Integrity in Pharmaceutical Quality Systems: A Risk-Based Approach. Journal of AI-Powered Medical Innovations (International online ISSN 3078-1930), 1(1), 83-104.
23. Pimpale, Siddhesh. (2021). Power Electronics Challenges and Innovations Driven by Fast- Charging EV Infrastructure. International Journal of Intelligent Systems and Applications in Engineering. 9. 144.
24. Archana, R., & Anand, L. (2023, May). Effective Methods to Detect Liver Cancer Using CNN and Deep Learning Algorithms. In 2023 International Conference on Advances in Computing, Communication and Applied Informatics (ACCAI) (pp. 1-7). IEEE.
25. Anumula, S. R. (2023). Enterprise architecture for real-time intelligence in distributed environments. International Journal of Computer Technology and Electronics Communication (IJCTEC), 6(4), 7301–7312.
26. Sabin Begum, R., & Sugumar, R. (2019). Novel entropy-based approach for cost-effective privacy preservation of intermediate datasets in cloud. Cluster Computing, 22(Suppl 4), 9581-9588.
27. Bellundagi, M. (2022). Performance Optimization Techniques for Enterprise Java Applications Using Middleware and Messaging Systems. International Journal of Computer Technology and Electronics Communication, 5(3), 5158-5168.
28. Namdeo, A. (2022). Graph neural networks for real-time supply chain risk. International Journal of Humanities and Information Technology, 4(1–3), 175–192.
29. Fung, J., & Panyala, V. R. (2020). Automating multi-region scalable CI/CD framework for managing AWS CloudWatch alerts. International Journal of Engineering & Extended Technologies Research, 2(5), 1854–1858.
30. Kasireddy, J. R. (2023). Operationalizing lakehouse table formats: A comparative study of Iceberg, Delta, and Hudi workloads. International Journal of Research Publications in Engineering, Technology and Management (IJRPETM), 6(2), 8371-8381.
31. Adari, V. K., Chunduru, V. K., Gonepally, S., Amuda, K. K., & Kumbum, P. K. (2023). Ethical analysis and decision-making framework for marketing communications: A weighted product model approach. Data Analytics and Artificial Intelligence, 3 (5), 44–53.
32. Madheswaran, M., Dhanalakshmi, R., Ramasubramanian, G., Aghalya, S., Raju, S., & Thirumaraiselvan, P. (2024, April). Advancements in immunization management for personalized vaccine scheduling with IoT and machine learning. In 2024 10th International Conference on Communication and Signal Processing (ICCSP) (pp. 1566-1570). IEEE.
33. Mohana, P., Muthuvinayagam, M., Umasankar, P., & Muthumanickam, T. (2022, March). Automation using Artificial intelligence based Natural Language processing. In 2022 6th International Conference on Computing Methodologies and Communication (ICCMC) (pp. 1735-1739). IEEE.
34. Chennamsetty, C. S. (2023). Standardizing Software Delivery: Unified Data Models and Scalable Infrastructure for Subscription Ecosystems. International Journal of Computer Technology and Electronics Communication, 6(2), 6658-6665.
35. Vimal Raja, G. (2024). Intelligent Data Transition in Automotive Manufacturing Systems Using Machine Learning. International Journal of Multidisciplinary and Scientific Emerging Research, 12(2), 515-518.
36. Rajan, P. K. (2023). Predictive Caching in Mobile Streaming Applications using Machine Learning Models. International Journal of Research Publications in Engineering, Technology and Management (IJRPETM), 6(3), 8737-8745.
37. Raju, S., & Sindhuja, D. (2024). Transparent encryption for external storage media with mobile-compatible key management by Crypto Ciphershield. PatternIQ Mining, 1(3), 12-24.
38. Surisetty, L. S. (2022). Designing Intelligent Integration Engines for Healthcare: From HL7 and X12 to FHIR and Beyond. International Journal of Advanced Research in Computer Science & Technology (IJARCST), 5(1), 5989-5998.
39. Ananth, S., & Saranya, A. (2016, January). Reliability enhancement for cloud services-a survey. In 2016 International Conference on Computer Communication and Informatics (ICCCI) (pp. 1-7). IEEE.
40. Adari, V. K. (2023). Intelligent Data Transition in Automotive Manufacturing Systems Using Machine Learning. International Journal of Multidisciplinary and Scientific Emerging Research, 12(2), 515-518.