AI-Enhanced Healthcare and Surgical Intelligence Real-Time Neural Network–Based Error Detection and Cloud QA with Oracle EBS Integration for Cross-Domain Finance
DOI:
https://doi.org/10.15662/IJEETR.2025.0706013Keywords:
Artificial Intelligence (AI), Surgical Intelligence, Healthcare Analytics, Real-Time Neural Networks, Error Detection, Cloud Quality Assurance, Oracle E-Business Suite (EBS), Cross-Domain Finance, Medical Imaging, Autonomous Anomaly Detection, Cloud Integration, Enterprise Workflow IntelligenceAbstract
This study presents an AI-enhanced framework integrating real-time neural network intelligence across healthcare, surgical systems, and financial workflows. The proposed architecture employs deep neural networks for autonomous error detection, anomaly prediction, and continuous cloud-based quality assurance, thereby reducing manual intervention and enhancing system reliability. By incorporating Oracle E-Business Suite (EBS), the framework ensures end-to-end transparency, auditability, and secure cross-domain process synchronization. The model supports surgical intelligence through rapid anomaly detection in medical imaging, operational workflows, and perioperative data streams, enabling timely interventions and improved clinical outcomes. Additionally, the system provides robust financial governance by validating and correcting transaction inconsistencies in real time. Experimental evaluation demonstrates significant improvements in detection accuracy, latency reduction, throughput enhancement, and workflow traceability. Overall, this research establishes a unified, scalable, and compliant AI-driven ecosystem bridging healthcare, surgical operations, and financial governance.
References
1. LeCun, Y., Bengio, Y., & Hinton, G. (2015). Deep learning. Nature, 521(7553), 436–444.
2. S. Roy and S. Saravana Kumar, “Feature Construction Through Inductive Transfer Learning in Computer Vision,” in Cybernetics, Cognition and Machine Learning Applications: Proceedings of ICCCMLA 2020, Springer, 2021, pp. 95–107.
Schmidhuber, J. (2017). Deep learning in neural networks: An overview. Neural Networks, 61, 85–117.
3. Urs, A. D. (2024). AI-Powered 3D Reconstruction from 2D Scans. International Journal of Humanities and Information Technology, 6(02), 30-36.
4. Kumar, R., Christadoss, J., & Soni, V. K. (2024). Generative AI for Synthetic Enterprise Data Lakes: Enhancing Governance and Data Privacy. Journal of Artificial Intelligence General science (JAIGS) ISSN: 3006-4023, 7(01), 351-366.
5. 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.
6. Mohile, A. (2022). Enhancing Cloud Access Security: An Adaptive CASB Framework for Multi-Tenant Environments. International Journal of Research Publications in Engineering, Technology and Management (IJRPETM), 5(4), 7134-7141.
7. Balaji, K. V., & Sugumar, R. (2023, December). Harnessing the Power of Machine Learning for Diabetes Risk Assessment: A Promising Approach. In 2023 International Conference on Data Science, Agents & Artificial Intelligence (ICDSAAI) (pp. 1-6). IEEE.
8. Kiran, A., Rubini, P., & Kumar, S. S. (2025). Comprehensive review of privacy, utility and fairness offered by synthetic data. IEEE Access.
9. Sivaraju, P. S. (2024). PRIVATE CLOUD DATABASE CONSOLIDATION IN FINANCIAL SERVICES: A CASE STUDY OF DEUTSCHE BANK APAC MIGRATION. ITEGAM-Journal of Engineering and Technology for Industrial Applications (ITEGAM-JETIA).
10. Adari, V. K. (2024). The Path to Seamless Healthcare Data Exchange: Analysis of Two Leading Interoperability Initiatives. International Journal of Research Publications in Engineering, Technology and Management (IJRPETM), 7(6), 11472-11480.
11. Konda, S. K. (2023). The role of AI in modernizing building automation retrofits: A case-based perspective. International Journal of Artificial Intelligence & Machine Learning, 2(1), 222–234. https://doi.org/10.34218/IJAIML_02_01_020
12. Rahman MM, Dhakal K, Gony N, Shuvra MK, Rahman M. AI integration in cybersecurity software: Threat detection and response. International Journal of Innovative Research and Scientific Studies [Internet]. 2025 May 26 [cited 2025 Aug 25];8(3):3907–21. Available from: https://www.ijirss.com/index.php/ijirss/article/view/7403
13. 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.
14. Sourav, M. S. A., Asha, N. B., & Reza, J. (2025). Generative AI in Business Analytics: Opportunities and Risks for National Economic Growth. Journal of Computer Science and Technology Studies, 7(11), 224-247.
15. Joseph, J. (2023). Trust, but Verify: Audit-ready logging for clinical AI. https://www.researchgate.net/profile/JimmyJoseph9/publication/395305525_Trust_but_Verify_Audit -ready_logging_for_clinical_AI/links/68bbc5046f87c42f3b9011db/Trust-but-Verify-Audit-readylogging-for-clinical-AI.pdf
16. Kusumba, S. (2025). Modernizing Healthcare Finance: An Integrated Budget Analytics Data Warehouse for Transparency and Performance. Journal of Computer Science and Technology Studies, 7(7), 567-573.
17. Ghosh, R., & Boyd, C. (2019). ERP modernization through intelligent automation. Oracle Journal, 33(4), 213–227.
18. Anderson, T. (2019). AI and compliance automation. IEEE Transactions on Systems, 36(4), 441–456.
19. Kandula, N. (2024). Optimizing Power Efficient Computer Architecture With A PROMETHEE Based Analytical Framework. J Comp Sci Appl Inform Technol, 9(2), 1-9.
20. Kakulavaram, S. R. (2024). “Intelligent Healthcare Decisions Leveraging WASPAS for Transparent AI Applications” Journal of Business Intelligence and DataAnalytics, vol. 1 no. 1, pp. 1–7. doi:https://dx.doi.org/10.55124/csdb.v1i1.261
21. Goriparthi, R. G. (2021). Scalable AI Systems for Real-Time Traffic Prediction and Urban Mobility Management. International Journal of Advanced Engineering Technologies and Innovations, 1(2), 255-278.
22. 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.
23. Archana, R., & Anand, L. (2023, September). Ensemble Deep Learning Approaches for Liver Tumor Detection and Prediction. In 2023 Third International Conference on Ubiquitous Computing and Intelligent Information Systems (ICUIS) (pp. 325-330). IEEE.
24. Chiranjeevi, Y., Sugumar, R., & Tahir, S. (2024, November). Effective Classification of Ocular Disease Using Resnet-50 in Comparison with Squeezenet. In 2024 IEEE 9th International Conference on Engineering Technologies and Applied Sciences (ICETAS) (pp. 1-6). IEEE.
25. Karanjkar, R. (2022). Resiliency Testing in Cloud Infrastructure for Distributed Systems. International Journal of Research Publications in Engineering, Technology and Management (IJRPETM), 5(4), 7142-7144.
