Smart Cloud-Integrated AI Model for Real-Time Medical Image Processing and Financial Quality Analysis in SAP

Authors

  • Saravana Kumar Subbiah Senior Project Lead, Wipro, Mexico Author

DOI:

https://doi.org/10.15680/IJCTECE.2025.0805018

Keywords:

Artificial Intelligence, Cloud Computing, SAP, Medical Image Processing, Real-Time Analysis, Financial Quality, Deep Learning, Data Integration

Abstract

The convergence of artificial intelligence (AI), cloud computing, and enterprise resource planning (ERP) systems has opened new avenues for intelligent data management across diverse sectors. This paper presents a Smart Cloud-Integrated AI Model designed to perform real-time medical image processing and financial quality analysis within SAP environments. The proposed system leverages cloud-based scalability and AI-driven analytics to simultaneously manage medical imaging workflows and financial data validation. Deep learning algorithms are employed to enhance diagnostic image clarity, anomaly detection, and classification accuracy, while financial modules within SAP are analyzed using AI-enabled quality metrics for error reduction and consistency assurance. Cloud integration ensures seamless data synchronization, security, and real-time access across distributed nodes. The model’s hybrid architecture bridges healthcare imaging intelligence with enterprise financial integrity, offering a unified platform that enhances decision-making, accuracy, and operational efficiency in real-time business and healthcare ecosystems

References

1. Kraus, M., & Feuerriegel, S. (2017). Decision support from financial disclosures with deep neural networks and transfer learning. arXiv. https://arxiv.org/abs/1710.03954

2. Konda, S. K. (2025). LEVERAGING CLOUD-BASED ANALYTICS FOR PERFORMANCE OPTIMIZATION IN INTELLIGENT BUILDING SYSTEMS. International Journal of Research Publications in Engineering, Technology and Management (IJRPETM), 8(1), 11770-11785.

3. Dr R., Sugumar (2023). Deep Fraud Net: A Deep Learning Approach for Cyber Security and Financial Fraud Detection and Classification (13th edition). Journal of Internet Services and Information Security 13 (4):138-157.

4. 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.

5. Bagam, N. (2021). Advanced techniques in predictive analytics for financial services. Integrated Journal for Research in Arts and Humanities, 1(1), 117–126. ijrah.com

6. David, L. K., Wang, J., Cisse, I. I., & Angel, V. (2024). Machine learning algorithms for financial risk prediction: A performance comparison. International Journal of Accounting Research, 9(2), 49–55. j.arabianjbmr.com

7. Karanjkar, R., & Karanjkar, D. (2024). Optimizing Quality Assurance Resource Allocation in Multi Team Software Development Environments. International Journal of Technology, Management and Humanities, 10(04), 49-59.

8. Kondra, S., Raghavan, V., & kumar Adari, V. (2025). Beyond Text: Exploring Multimodal BERT Models. International Journal of Research Publications in Engineering, Technology and Management (IJRPETM), 8(1), 11764-11769.

9. Antwi, B. O., & Avickson, E. K. (2024). Integrating SAP, AI and data analytics for advanced enterprise management. International Journal of Research Publication and Reviews, 5(10), 621–636. ResearchGate

10. Gosangi, S. R. (2023). Transforming Government Financial Infrastructure: A Scalable ERP Approach for the Digital Age. International Journal of Humanities and Information Technology, 5(01), 9-15.

11. Jannatul, F., Md Saiful, I., Md, S., & Gul Maqsood, S. (2025). AI-Driven Investment Strategies Ethical Implications and Financial Performance in Volatile Markets. American Journal of Business Practice, 2(8), 21-51.

12. Sivaraju, P. S., & Mani, R. (2024). Private Cloud Database Consolidation in Financial Services: A Comprehensive Case Study on APAC Financial Industry Migration and Modernization Initiatives. International Journal of Research Publications in Engineering, Technology and Management (IJRPETM), 7(3), 10472-10490.

13. Komarina, G. B. (2024). Transforming Enterprise Decision-Making Through SAP S/4HANA Embedded Analytics Capabilities. Journal ID, 9471, 1297.

14. 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.

15. Hoshiar Singh, P. (2024). AI Driven financial data analytics: Unleashing the power of SAP FICO for predictive accounting. ESP IJACT, 2(3), 153–166. ESP Journals

16. Das, S. K., Tulsyan, U., Dwadas, V. S. A., Jilani, S., & Kumar Y., S. (2024). AI powered predictive analytics in financial forecasting: Implications for corporate planning and risk management. International Journal of Intelligent Systems and Applications in Engineering, 12(21s), 3512–3516. IJISAE

17. Zheng, X., Zhu, M., Li, Q., Chen, C., & Tan, Y. (2018). FinBrain: When finance meets AI 2.0. arXiv. https://arxiv.org/abs/1808.08497 arXiv

18. Christadoss, J., Kalyanasundaram, P. D., & Vunnam, N. (2024). Hybrid GraphQL-FHIR Gateway for Real-Time Retail-Health Data Interchange. Essex Journal of AI Ethics and Responsible Innovation, 4, 204-238.

19. Manda, P. (2022). IMPLEMENTING HYBRID CLOUD ARCHITECTURES WITH ORACLE AND AWS: LESSONS FROM MISSION-CRITICAL DATABASE MIGRATIONS. International Journal of Research Publications in Engineering, Technology and Management (IJRPETM), 5(4), 7111-7122.

20. Kumar, D., & Wong, A. (2017). Opening the black box of financial AI with CLEAR Trade: A class enhanced attentive response approach for explaining and visualizing deep learning driven stock market prediction. arXiv. https://arxiv.org/abs/1709.01574 arXiv

21. Dr R., Sugumar (2023). Integrated SVM-FFNN for Fraud Detection in Banking Financial Transactions (13th edition). Journal of Internet Services and Information Security 13 (4):12-25.

22. Kumar, A., Anand, L., & Kannur, A. (2024, November). Optimized Learning Model for Brain-Computer Interface Using Electroencephalogram (EEG) for Neuroprosthetics Robotic Arm Design for Society 5.0. In 2024 International Conference on Computing, Semiconductor, Mechatronics, Intelligent Systems and Communications (COSMIC) (pp. 30-35). IEEE.

23. 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.

24. 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.

25. A. K. S, L. Anand and A. Kannur, "A Novel Approach to Feature Extraction in MI - Based BCI Systems," 2024 8th International Conference on Computational System and Information Technology for Sustainable Solutions (CSITSS), Bengaluru, India, 2024, pp. 1-6, doi: 10.1109/CSITSS64042.2024.10816913.

26. Lora, S. (2024). Transform financial data into strategic insights using the SAP Business Technology Platform. Journal of Global Economy, Business and Finance, 6(10), 06. bryanhousepub.com

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Published

2025-10-15

How to Cite

Smart Cloud-Integrated AI Model for Real-Time Medical Image Processing and Financial Quality Analysis in SAP. (2025). International Journal of Computer Technology and Electronics Communication, 8(5), 11428-11432. https://doi.org/10.15680/IJCTECE.2025.0805018