AI-Driven Cloud and Oracle-Based Machine Learning Architecture for Predictive Analytics in Healthcare and Banking Systems
DOI:
https://doi.org/10.15662/IJARCST.2025.0806803Keywords:
AI-driven cloud, Oracle Machine Learning, predictive analytics, healthcare systems, banking systems, cloud computing, data intelligence, risk predictionAbstract
The rapid convergence of Artificial Intelligence (AI), Cloud Computing, and Machine Learning (ML) has transformed data-driven decision-making across critical sectors such as healthcare and banking. This paper presents an AI-driven cloud architecture integrated with Oracle-based Machine Learning tools to enhance predictive analytics, data security, and operational efficiency. The proposed system leverages Oracle Cloud Infrastructure (OCI) for scalable data management, AI models for intelligent pattern recognition, and ML algorithms for real-time prediction of risks and trends. In healthcare, the architecture enables early disease detection, patient monitoring, and treatment optimization, while in banking, it supports fraud detection, credit risk assessment, and customer behavior analysis. The research demonstrates how a unified Oracle-enabled AI-ML cloud framework can ensure high performance, interoperability, and compliance with data governance standards. The study concludes that integrating AI-driven predictive analytics within Oracle Cloud can significantly improve decision accuracy, reduce latency, and enhance the overall reliability of healthcare and financial ecosystems.
References
1. Bennett, C., Doub, T., & Selove, R. (2012). EHRs connect research and practice: Where predictive modeling, artificial intelligence, and clinical decision support intersect. arXiv preprint arXiv:1204.4927. arXiv
2. Archana, R., & Anand, L. (2025). Residual u-net with Self-Attention based deep convolutional adaptive capsule network for liver cancer segmentation and classification. Biomedical Signal Processing and Control, 105, 107665.
3. Manda, P. (2025). DISASTER RECOVERY BY DESIGN: BUILDING RESILIENT ORACLE DATABASE SYSTEMS IN CLOUD AND HYPERCONVERGED ENVIRONMENTS. International Journal of Research and Applied Innovations, 8(4), 12568-12579.
4. Kiran, A., Rubini, P., & Kumar, S. S. (2025). Comprehensive review of privacy, utility and fairness offered by synthetic data. IEEE Access.
5. Arulraj AM, Sugumar, R., Estimating social distance in public places for COVID-19 protocol using region CNN, Indonesian Journal of Electrical Engineering and Computer Science, 30(1), pp.414-424, April 2023.
6. Perumalsamy, J., & Christadoss, J. (2024). Predictive Modeling for Autonomous Detection and Correction of AI-Agent Hallucinations Using Transformer Networks. Journal of Artificial Intelligence General science (JAIGS) ISSN: 3006-4023, 6(1), 581-603.
7. Ponnoju, S. C., Kotapati, V. B. R., & Mani, K. (2022). Enhancing Cloud Deployment Efficiency: A Novel Kubernetes-Starling Hybrid Model for Financial Applications. American Journal of Autonomous Systems and Robotics Engineering, 2, 203-240.
8. Adari, Vijay Kumar, “Interoperability and Data Modernization: Building a Connected Banking Ecosystem,” International Journal of Computer Engineering and Technology (IJCET), vol. 15, no. 6, pp.653-662, Nov-Dec 2024. DOI:https://doi.org/10.5281/zenodo.14219429.
9. Shashank, P. S. R. B., Anand, L., & Pitchai, R. (2024, December). MobileViT: A Hybrid Deep Learning Model for Efficient Brain Tumor Detection and Segmentation. In 2024 International Conference on Progressive Innovations in Intelligent Systems and Data Science (ICPIDS) (pp. 157-161). IEEE.
10. Kandula, N. (2025). FALCON 2.0 SNAPPY REPORTS A NOVEL TOPSIS-DRIVEN APPROACH FOR REAL-TIME MULTI-ATTRIBUTE DECISION ANALYSIS. International Journal of Computer Engineering and Technology. https://d1wqtxts1xzle7.cloudfront.net/123658421/IJCET_16_03_025-libre.pdf?1751969013=&response-content-disposition=inline%3B+filename%3DFALCON_2_0_SNAPPY_REPORTS_A_NOVEL_TOPSIS.pdf&Expires=1762455977&Signature=VIqzvY3p06lIX7qtLK3gQ4J4m~jRp8r3Avl6Ue~B6mr~oQBzgji7KpLf2~uCE3wreoG5iRGiGyBg1t4B8zroSOP2208fO3a4eU~usNiBPQvvch5wneEaqJGhZ3bz-EEsc12OWDxn~5JUkA31zgeAnzRGWtHdGiMIAe3ghx1cPszPHY8ofzYZW3PnBcqp5cMRwVpZohCCVxagHfC-fLJFg5FwkeHH5xXudx8V-ESt~nTaYGTm72LGRlmrYOdl3tXN4GxDL25vgqf3244EFjJktGvWy7gk7vr5epKFK-l5DDAAIhddtH2~AnwT7evLUZeyHZdQalpa83r2YBuiSct2Lg__&Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA
11. Shakil, K. A., Zareen, F. J., Alam, M., & Jabin, S. (2017). BAMHealthCloud: A biometric authentication and data management system for healthcare data in cloud. arXiv preprint arXiv:1705.07121. arXiv
12. Kesavan, E. (2025). Software Bug Prediction Using Machine Learning Algorithms: An Empirical Study on Code Quality and Reliability. International Journal of Innovations in Science, Engineering And Management, 377-381.
13. Sridhar Kakulavaram. (2024). Artificial Intelligence-Driven Frameworks for Enhanced Risk Management in Life Insurance. Journal of Computational Analysis and Applications (JoCAAA), 33(08), 4873–4897. Retrieved from https://www.eudoxuspress.com/index.php/pub/article/view/2996
14. Phani Santhosh Sivaraju, 2025. "Phased Enterprise Data Migration Strategies: Achieving Regulatory Compliance in Wholesale Banking Cloud Transformations," Journal of Artificial Intelligence General science (JAIGS) ISSN:3006- 4023, Open Knowledge, vol. 8(1), pages 291-306.
15. Sakhawat Hussain, T., Md Manarat Uddin, M., & Rahanuma, T. (2025). Sustaining Vital Care in Disasters: AI-Driven Solar Financing for Rural Clinics and Health Small Businesses. American Journal of Technology Advancement, 2(9), 123-153.
16. Khan, M. I. (2025). MANAGING THREATS IN CLOUD COMPUTING: A CYBERSECURITY RISK MITIGATION FRAMEWORK. International Journal of Advanced Research in Computer Science, 15(5). https://www.researchgate.net/profile/Md-Imran-Khan-12/publication/396737007_MANAGING_THREATS_IN_CLOUD_COMPUTING_A_CYBERSECURITY_RISK_MITIGATION_FRAMEWORK/links/68f79392220a341aa156b531/MANAGING-THREATS-IN-CLOUD-COMPUTING-A-CYBERSECURITY-RISK-MITIGATION-FRAMEWORK.pdf
17. Adari, V. K. (2024). How Cloud Computing is Facilitating Interoperability in Banking and Finance. International Journal of Research Publications in Engineering, Technology and Management (IJRPETM), 7(6), 11465-11471.
18. Peddamukkula, P. K. Advanced Fraud Prevention Frameworks in Financial Services: Leveraging Cloud Computing, Data Modernization, and Automation Technologies. https://www.researchgate.net/profile/Praveen-Peddamukkula/publication/396983756_Advanced_Fraud_Prevention_Frameworks_in_Financial_Services_Leveraging_Cloud_Computing_Data_Modernization_and_Automation_Technologies/links/6900dcf9368b49329fa787fc/Advanced-Fraud-Prevention-Frameworks-in-Financial-Services-Leveraging-Cloud-Computing-Data-Modernization-and-Automation-Technologies.pdf
19. Leonard, D., & Others (hypothetical or similar studies) – omitted here as not directly identified prior to 2024 but implicit in reviews.
20. Lin, T. (2025). Enterprise AI governance frameworks: A product management approach to balancing innovation and risk. International Research Journal of Management, Engineering, Technology, and Science, 1(1), 123–145. https://doi.org/10.56726/IRJMETS67008.
21. Sankar, Thambireddy,. (2024). SEAMLESS INTEGRATION USING SAP TO UNIFY MULTI-CLOUD AND HYBRID APPLICATION. International Journal of Engineering Technology Research & Management (IJETRM), 08(03), 236–246. https://doi.org/10.5281/zenodo.15760884
22. Kiran, A., & Kumar, S. A methodology and an empirical analysis to determine the most suitable synthetic data generator. IEEE Access 12, 12209–12228 (2024).
23. Gosangi, S. R. (2023). AI AND THE FUTURE OF PUBLIC SECTOR ERP: INTELLIGENT AUTOMATION BEYOND DATA ANALYTICS. International Journal of Research Publications in Engineering, Technology and Management (IJRPETM), 6(4), 8991-8995.
24. Sudhan, S. K. H. H., & Kumar, S. S. (2015). An innovative proposal for secure cloud authentication using encrypted biometric authentication scheme. Indian journal of science and technology, 8(35), 1-5.
25. Poornima, G., & Anand, L. (2025). Medical image fusion model using CT and MRI images based on dual scale weighted fusion based residual attention network with encoder-decoder architecture. Biomedical Signal Processing and Control, 108, 107932.
26. Sugumar, R. (2022). Estimation of Social Distance for COVID19 Prevention using K-Nearest Neighbor Algorithm through deep learning. IEEE 2 (2):1-6.
27. “Integrating Artificial Intelligence and Machine Learning into Healthcare ERP Systems: A Framework for Oracle Cloud and Beyond.” Singh, V., Pathak, D., & Gupta, P. (2023). ESP Journal of Engineering & Technology Advancements. espjeta.org
