Advanced Smart Clinical Decision Support Frameworks using Generative AI and Edge-Cloud Computing
DOI:
https://doi.org/10.15680/IJMRSETM.2025.0103014Keywords:
Generative AI, Clinical Decision Support Systems, Edge Computing, Cloud Computing, Smart Healthcare, Predictive Analytics, Personalized Medicine, Real-Time Monitoring, Healthcare AutomationAbstract
Advanced smart clinical decision support frameworks are undergoing a major transformation through the integration of generative artificial intelligence (AI) and edge–cloud computing architectures. These systems aim to enhance clinical decision-making by combining real-time data processing at the edge with large-scale analytical capabilities in the cloud. Generative AI models, particularly large language and multimodal models, enable the synthesis of complex medical knowledge, interpretation of clinical data, and generation of personalized treatment recommendations. Meanwhile, edge computing facilitates low-latency processing of patient data from wearable devices, medical sensors, and bedside monitoring systems, ensuring timely interventions in critical scenarios. The cloud layer complements this by providing scalable infrastructure for model training, data storage, and cross-institutional collaboration. This hybrid framework addresses key challenges in healthcare such as data fragmentation, delayed diagnosis, and inefficient resource utilization. However, issues related to data privacy, model interpretability, and system integration remain significant concerns. This paper explores the architecture, methodologies, and advantages of such frameworks, emphasizing their potential to revolutionize healthcare delivery by enabling proactive, personalized, and efficient clinical decision support systems while ensuring scalability and adaptability across diverse healthcare environments
References
1. Yamsani, N. (2016). Advancing Data Consistency and Control Across Global Financial Institutions by Enterprise Master Data Platforms. International Journal of Technology, Management and Humanities, 2(01), 22-35.
2. Guda, D. P. (2024). Cyber insurance for DevSecOps risks: Pricing models and coverage gaps. Journal of Information Systems Engineering and Management, 9(3).
3. Mudusu, S. K. (2025). AI-driven data engineering in the Internet of Things: Scaling data pipelines for smart device ecosystems. ISCSITR-International Journal of Data Engineering (ISCSITR-IJDE), 6(1), 1–9.
4. Adepu, G. (2025). AI-based epidemiological data platforms for early outbreak detection and real-time health analytics. International Journal of Future Innovative Science and Technology (IJFIST), 8(2), 9–29.
5. Vankayala, S. C. (2020). Reinventing test automation reliability: Adaptive locator intelligence and self-healing execution pipelines for enterprise QA. International Journal of Scientific Research in Computer Science, Engineering and Information Technology, 6(1), 226–242. https://doi.org/10.32628/CSEIT23906127.
6. Kasireddy, J. R. (2025). The transformative role of AI and machine learning in financial risk analysis. World Journal of Advanced Research and Reviews, 26(1), 1246–1256. https://doi.org/10.30574/wjarr.2025.26.1.1177
7. Karvannan, R. (2024). Ensuring Patient Safety and Regulatory Compliance with Advanced Pharmaceutical Supply Chain Systems. International Journal of Advanced Research in Computer Science & Technology (IJARCST), 7(6), 11334-11344.
8. Rahman, M. B., Yasin, M., & Ahmed, M. P. (2024). Data-Driven Population Health Analytics for Identifying High-Risk Groups and Health Disparities. American Journal Of Botany And Bioengineering, 1(11), 58-82.
9. Parupalli, A., & Pandya, S. (2022). Compliance-Driven Data Governance: A Survey on GDPR, and HIPAA in Cloud Databases. vol, 12, 828-836.
10. Panda, S. S. (2025). Redefining cloud-native performance: A technical evaluation of Microsoft Azure’s Cobalt 100 ARM-based virtual machines. International Journal of Research Publications in Engineering, Technology and Management (IJRPETM), 8(2), 11815–11830.
11. Bellundagi, M. (2023). Blockchain-Based Secure Data Sharing Framework for Smart Applications. International Journal of Future Innovative Science and Technology (IJFIST), 6(2), 10268.
12. Hossain, M. S., Ali, M., & HOSSAIN, M. S. (2023). AI-Enhanced Labor Market Analytics to Predict Workforce Shifts and Support Policy Decisions in the US Economy. Journal of Computer Science and Technology Studies, 5(1), 101-120.
13. Ambalakannu, M. (2025). Accelerating Claims Processing with Observability and Automated Dashboards. International Journal of Advanced Research in Computer Science & Technology (IJARCST), 8(3), 12179-12186.
14. Mallireddy, S. (2024). Trusting ServiceNow AI to deliver business value. International Journal of Research and Applied Innovations (IJRAI), 7(5), 55–58.
15. Gopinathan, V. R. (2025). Intelligent workload scheduling for telecom cloud architecture using reinforcement learning. International Journal of Research Publications in Engineering, Technology and Management (IJRPETM), 8(6), 13244-13255.
16. Narayanan, S. (2024). Cyber risk orchestration for systemic financial stability: An autonomous financial impact forecasting. International Journal of Research in Computer Applications and Information Technology, 7(2), 2927–2939. https://philarchive.org/archive/NARCRO
17. Vayyasi, N. K. (2023). Designing a multi-domain predictive framework using Java and generative AI for financial, retail, and industrial use cases. International Journal of Computer Technology and Electronics Communication (IJCTEC), 6(6), 8060–8069.
18. Rao, G. R. (2023). Hidden Trade-Offs in Modern Frontend Architecture. International Journal of Computer Technology and Electronics Communication, 6(5), 7615-7625.
19. Rajendran, S., Sundarapandi, A. M. S., Krishnamurthy, A., & Thanarajan, T. (2022). An intelligent face recognition technology for iot-based smart city application using condition-cnn with foraging learning pso model. International Journal of Pattern Recognition and Artificial Intelligence, 36(14), 2256018.
20. Gentyala, R. (2024). Breaking or Reinforcing the Cycle? Longitudinal Impacts of Bias-Correction Techniques on Feedback Loops and Sustained Financial Inclusion in Machine Learning Credit Scoring. American International Journal of Computer Science and Technology, 6(5), 44-56.
21. Parasa, M. (2023). Measuring skill graph drift in SAP SuccessFactors Talent Intelligence Hub for career mobility, workforce reskilling, and skills-based talent governance. Advanced International Journal of Multidisciplinary Research, 1(1), 1–27. https://doi.org/10.62127/aijmr.2023.v01i01.1359
22. Subramanyam, S. P. (2025). AI-driven CI/CD pipeline automation for secure .NET applications in Azure Kubernetes Services. International Journal of Science, Research and Technology (IJSRAT), 8(1), 13505–13512. https://doi.org/10.15662/IJSRAT.2025.0801003
23. Namdeo, A. (2022). Federated learning BI across multi-cloud data silos. The International Journal of Research Publications in Engineering, Technology and Management, 5(6), 7893–7903.
24. Karnam, V. S. (2025). Leveraging Intelligent Predictive Analytics Using AI in Cloud-Based Safety and Security Operations for Transforming Disaster and Emergency Management Response. Journal of Computer Science and Technology Studies, 7(7), 660-667.
25. Soundappan, S. J. (2021). DataOps: Orchestrating Reliable ML Data Pipelines. International Journal of Research and Applied Innovations, 4(4), 5533-5537.
26. Nallamothu, T. K. (2023). Generative AI in healthcare: Automating clinical documentation, diagnostics, and knowledge synthesis. International Journal of Computer Technology and Electronics Communication, 6(1), 6376–6392.
27. Sharma, K. P., Kumar, I., Singh, P. P., Anbazhagan, K., Albarakati, H. M., Bhatt, M. W., ... & Rana, A. (2024). Advancing spacecraft rendezvous and docking through safety reinforcement learning and ubiquitous learning principles. Computers in Human Behavior, 153, 108110.
28. Boddupally, H. L. (2024). Embedding Governance into LLM Workflow Architectures for Enterprise-Wide Automation. International Journal of Scientific Research in Computer Science, Engineering and Information Technology, 10(7), 279-294.
29. Mathew, A. (2024). Cloud data sovereignty governance and risk implications of cross-border cloud storage. Information Systems Audit and Control Association.
30. Appani, C. (2024). Explainable AI for fraud detection in financial transactions. Journal of Information Systems Engineering and Management, 9(3). https://jisem-journal.com/download/32_Explainable_AI_for_Fraud_Detection.pdf
31. Lanka, S. (2024). Redefining Digital Banking: ANZ’s Pioneering Expansion into Multi-Wallet Ecosystems. International Journal of Technology, Management and Humanities, 10(01), 33-41.
32. Pothuri, M. K. Building a Seamless Healthcare Data Fabric: Zero-Touch Integration and Scalable Mapping Across Provider, Claims, Recipient, and Pharmacy Source Systems for State Medicaid. IJLRP-International Journal of Leading Research Publication, 6(8).
33. Adepu, R. (2024). Secure cloud migration strategies for enterprise data center modernization. International Journal of Engineering & Extended Technologies Research (IJEETR), 6(6), 239–258.
34. Soujanya, T., Alsalami, Z., Srinath, S., Sengupta, J., & Das, A. (2024, May). Rooftop Photovoltaic Panel Segmentation using Improved Mask Region-based Convolutional Neural Network. In 2024 Second International Conference on Data Science and Information System (ICDSIS) (pp. 1-4). IEEE.
35. Devineni, A. (2024). Causal Inference in Distributed Tracing: Automating Root Cause Analysis in Complex Microservice Dependencies. International Journal of Emerging Trends in Computer Science and Information Technology, 5(4), 166-173.
36. Aashiq Banu, S., Rao, L. K., Priya, P. S., Thanikaiselvan, Hemalatha, M., Dhivya, R., & Rengarajan, A. (2025). A review of genome to chaos: exploring DNA dynamics in security. Multimedia Tools and Applications, 84(22), 24859-24886.
37. Dave, B. L. (2024). Future-proof living leading a better life with artificial intelligence. International Journal of Research Publications in Engineering, Technology and Management (IJRPETM), 7(5), 11233–11242.
38. Balamuralidhar Sarabu, V. (2025). Architecting scalable data integration frameworks for hybrid enterprise platforms with strong data governance. International Journal of Advanced Research in Computer Science & Technology, 8(3), 149–164.
39. Mali, R. K. (2023). A Scalable Microservice Framework for Multi-Modal Logistics Route Optimization. International Journal of Research Publications in Engineering, Technology and Management (IJRPETM), 6(2), 8382-8391.
40. Suddala, V. R. A. K. (2025). Building scalable, secure, and compliance-ready healthcare e-commerce platforms in regulated environment. International Journal of Research and Applied Innovations, 8(4), 12699–12710.
41. Kunadi, S. K. (2021). Establishing robust data foundations: Early-stage architecture for scalable data warehousing and analytics systems. International Journal of Engineering & Extended Technologies Research (IJEETR), 3(3), 3078–3088.
