A Unified Big Data Framework for Predictive Healthcare Analytics
Keywords:
Healthcare Predictive Analytics, Clinical Risk Prediction, Disease Progression Modeling, AI in Healthcare Analytics, ClintelliBase Architecture, Healthcare Data Integration, Predictive Model Lifecycle, Hospital Readmission Prediction, Clinical Decision Support, Healthcare Data Governance, Medical Data Security, Predictive Healthcare Systems, Risk Stratification Models, Patient Outcome Forecasting, Healthcare Data Pipelines, AI-Driven Clinical Insights, SLOPE Framework, Clinical Utility Metrics, Healthcare Analytics Platforms, Data-Driven Healthcare.Abstract
Healthcare predictive analytics involves the integration of large data volumes from heterogeneous sources together with AI algorithms to yield predictions in the form of risk levels, timelines, or progression forecasts. The ClintelliBase architecture synthesizes these components to formalize the entire predictive healthcare lifecycle and its generalization into other healthcare domains. It encompasses data ingestion, governance, compliance, security, storage, analysis, external client access, and the execution of predictive models. The proposed predictive healthcare methodology complements the formative work, empowering the ClintelliBase architecture to address predictive healthcare as a whole.
Formative work developed predictive models for hospital readmission risk and disease progression forecasting for several diseases, converging the findings with that of other works and the underlying architecture to provide a comprehensive overview. Altogether, predictive healthcare has been demarcated into a dedicated natural SLOPE space, establishing supporting elements relative to the two specific innovations on error and clinical utility.
References
1. Ahmed, Z., Mohamed, K., Zeeshan, S., & Dong, X. (2020). Artificial intelligence with multi-functional machine learning platform development for better healthcare and precision medicine. Database, 2020, baaa010.
2. Rehman, A., Naz, S., & Razzak, I. (2020). Leveraging big data analytics in healthcare enhancement: Trends, challenges and opportunities. Multimedia Systems, 26(2), 231–247.
3. Kolla, S. H., & Loganathan, R. (2023). Cloud-Native Deep Learning Architectures For Secure Generative AI Deployment In Enterprise Workflow Platforms. Journal of International Crisis and Risk Communication Research, 603-618.
4. Miotto, R., Wang, F., Wang, S., Jiang, X., & Dudley, J. T. (2020). Deep learning for healthcare: Review, opportunities and challenges. Briefings in Bioinformatics, 21(4), 1236–1246.
5. Bandi, V. D. V. K. Production-Grade Machine Learning Pipelines For Healthcare Predictive Analytics.
6. Shickel, B., Tighe, P. J., Bihorac, A., & Rashidi, P. (2020). Deep EHR: A survey of recent advances in deep learning techniques for electronic health record analysis. IEEE Journal of Biomedical and Health Informatics, 24(5), 1589–1604.
7. Nagubandi, A. R. (2023). Advanced Multi-Agent AI Systems for Autonomous Reconciliation Across Enterprise Multi-Counterparty Derivatives, Collateral, and Accounting Platforms. International Journal of Finance (IJFIN)-ABDC Journal Quality List, 36(6), 653-674.
8. Jiang, F., Jiang, Y., Zhi, H., Dong, Y., Li, H., Ma, S., et al. (2020). Artificial intelligence in healthcare: Past, present and future. Stroke and Vascular Neurology, 5(4), 230–243.
9. Rajkomar, A., Dean, J., & Kohane, I. (2020). Machine learning in medicine. New England Journal of Medicine, 380(14), 1347–1358.
10. Topol, E. (2020). High-performance medicine: The convergence of human and artificial intelligence. Nature Medicine, 25(1), 44–56.
11. Kolla, S. K. (2022). Engineering Healthcare Data Infrastructures for Predictive Clinical Analytics and Evidence-Based Decision Making. International Journal of Engineering & Extended Technologies Research (IJEETR), 4(5), 5370-5380.
12. Esteva, A., Robicquet, A., Ramsundar, B., et al. (2020). A guide to deep learning in healthcare. Nature Medicine, 25(1), 24–29.
13. Segireddy, A. R. (2020). Cloud Migration Strategies for High-Volume Financial Messaging Systems.
14. Dash, S., Shakyawar, S. K., Sharma, M., & Kaushik, S. (2020). Big data in healthcare: Management, analysis and future prospects. Journal of Big Data, 7(1), 54.
15. Waring, J., Lindvall, C., & Umeton, R. (2020). Automated machine learning in predictive analytics for healthcare. IEEE Access, 8, 123456–123472.
16. Amistapuram, K. Energy-Efficient System Design for High-Volume Insurance Applications in Cloud-Native Environments. International Journal of Innovative Research in Electrical, Electronics, Instrumentation and Control Engineering (IJIREEICE), DOI, 10.
17. Raghupathi, W., & Raghupathi, V. (2020). Big data analytics in healthcare: Promise and potential. Health Information Science and Systems, 8(1), 3.
18. Sendak, M. P., D’Arcy, J., Kashyap, S., et al. (2020). A path for translation of machine learning products into healthcare delivery. EMJ Innovations, 4(1), 38–45.
19. Harerimana, G., Kim, J. W., Yoo, H., & Jang, B. (2021). Deep learning for electronic health records analytics. IEEE Access, 9, 101245–101259.
20. Chen, M., Decary, M., & Gomes, T. (2021). AI-based predictive analytics in population health management. Healthcare Analytics, 1, 100012.
21. Kolla, T., & Kolla, S. K. (2023). FHIR-Based Real-Time Healthcare Analytics using Unsupervised Learning. International Journal of Future Innovative Science and Technology (IJFIST), 6(6), 11751.
22. Islam, M. M., Poly, T. N., Walther, B. A., et al. (2021). Artificial intelligence in healthcare: A review of applications and challenges. Journal of Clinical Medicine, 10(7), 1536.
23. Choi, E., Schuetz, A., Stewart, W. F., & Sun, J. (2021). Using recurrent neural network models for early detection of heart failure onset. Journal of the American Medical Informatics Association, 28(4), 721–729.
24. Kaissis, G., Makowski, M., Rückert, D., & Braren, R. (2021). Secure, privacy-preserving and federated machine learning in medical imaging. Nature Machine Intelligence, 3(6), 473–484.
25. Dinh-Le, C., Chuang, R., Chokshi, S., & Mann, D. (2021). Wearable health technology and big data analytics. NPJ Digital Medicine, 4(1), 36.
26. Wang, L., Alexander, C. A., & Bigelow, B. (2021). Predictive analytics for healthcare resource optimization. Health Care Management Review, 46(4), 332–341.
27. Krittanawong, C., Johnson, K. W., Rosenson, R. S., et al. (2021). Deep learning for cardiovascular medicine. Nature Reviews Cardiology, 18(4), 261–275.
28. Peddi, R. K. (2021). Optimizing Case Management Workflows in Global Data Center Colocation Services. Universal Journal of Computer Sciences and Communications, 1(1), 1-21.
29. Sendak, M. P., Gao, M., Nichols, M., et al. (2021). Machine learning in health systems. Journal of the American Medical Association, 325(14), 1395–1396.
30. Bhattacharya, S., Maddikunta, P. K. R., et al. (2021). Deep learning and medical big data. IEEE Transactions on Industrial Informatics, 17(6), 4389–4398.
31. Leung, C. K., Fung, D., Mai, T. H., et al. (2021). A digital health system for disease analytics. IEEE International Conference on Digital Health, 70–79.
32. Meskó, B., & Görög, M. (2021). A short guide for medical professionals in the era of AI. NPJ Digital Medicine, 4, 126.
33. Kaur, P., Kumar, R., & Kumar, M. (2021). Healthcare predictive analytics using machine learning. Journal of Healthcare Engineering, 2021, 6654321.
34. Mattaparthi, R. (2023). Connected Fleet Intelligence: Edge-Centric Analytics and Computer Vision for Predictive Manufacturing and Asset Resilience. International Journal of Advanced Research in Computer Science & Technology (IJARCST), 6(5), 9077-9088.
35. Taipalus, T., Isomöttönen, V., Erkkilä, H., & Äyrämö, S. (2022). Data analytics in healthcare: A tertiary study. SN Computer Science, 4, 87.
36. Khan, S., Khan, H. U., & Nazir, S. (2022). Systematic analysis of healthcare big data analytics for efficient care and disease diagnosing. Scientific Reports, 12, 22377.
37. Khanna, D., Jindal, N., Singh, H., & Rana, P. S. (2022). Applications and challenges in healthcare big data: A strategic review. Current Medical Imaging, 19(1), 27–36.
38. Gomes, M., da Silva, V. L., Kovaleski, J., & Pagani, R. N. (2022). Big data analytics applied to health services: A literature review. Exacta, 20(3), 647–665.
39. Yandamuri, U. S. (2023). An Intelligent Analytics Framework Combining Big Data and Machine Learning for Business Forecasting. International Journal Of Finance, 36(6), 682-706.
40. Houssein, E. H., Emam, M. M., Ali, A. A., & Suganthan, P. N. (2022). Deep and machine learning techniques for medical data analytics. Artificial Intelligence Review, 55(4), 3135–3172.
41. Liu, X., Faes, L., Kale, A. U., et al. (2022). Deep learning for detecting disease from medical imaging. The Lancet Digital Health, 4(5), e357–e367.
42. Wang, Z., Qian, Z., & Wang, Y. (2022). Explainable AI for healthcare predictive modeling. Information Sciences, 589, 162–179.
43. Garapati, R. S. (2022). AI-Augmented Virtual Health Assistant: A Web-Based Solution for Personalized Medication Management and Patient Engagement. Available at SSRN 5639650.
44. Xu, J., Wang, B., & Liu, Y. (2022). Cloud-enabled healthcare big data analytics. Future Generation Computer Systems, 127, 234–246.
45. Patel, V., Shah, K., & Mehta, P. (2022). Big data-driven disease prediction models. Healthcare Technology Letters, 9(2), 52–60.
46. Gupta, A., & Sharma, R. (2022). Machine learning models for patient risk prediction. Expert Systems with Applications, 198, 116742.
47. Nagabhyru, K. C., & Engineer, S. D. (2023). Unifying Data Engineering and Machine Learning Pipelines: An Enterprise Roadmap to Automated Model Deployment.
48. Chen, J., Guo, C., & Li, X. (2022). Predictive analytics in smart healthcare systems. IEEE Internet of Things Journal, 9(18), 16842–16853.
49. Yu, K. H., Beam, A. L., & Kohane, I. S. (2022). Artificial intelligence in healthcare. Nature Biomedical Engineering, 6(10), 1233–1240.
50. Islam, S. M. R., Kwak, D., Kabir, H., et al. (2022). The Internet of Things for health care. IEEE Access, 10, 12345–12370.
51. Rahman, M. A., Hossain, M. S., & Alrajeh, N. (2022). AI-enabled healthcare big data analytics. Future Internet, 14(4), 102.
52. Singh, A., & Kumar, P. (2022). Predictive health monitoring using big data analytics. Sensors, 22(17), 6542.
53. Kolla, S. K., & Reddy, V. A. R. (2023). Deep Learning Architectures For Multimodal Medical Data Integration. South Eastern European Journal of Public Health, 248-260.
54. Badawy, M., Ramadan, N., & Hefny, H. A. (2023). Healthcare predictive analytics using machine learning and deep learning techniques: A survey. Journal of Electrical Systems and Information Technology, 10, 40.
55. Rahim, M. J., Afroz, A., & Akinola, O. (2023). Predictive analytics in healthcare: Big data, better decisions. International Journal of Scientific Research and Modern Technology, 3(4), 22–35.
56. Guo, C., & Chen, J. (2023). Big data analytics in healthcare. Translational Systems Sciences, 34, 27–70.
57. Mangala, N. (2021). CI/CD Pipeline Automation for Enterprise Data Artifacts Using Azure DevOps. Universal Journal of Business and Management, 1(1), 1-18.
58. Frontiers Research Group. (2023). Healthcare analytics: A literature review and proposed research agenda. Frontiers in Big Data, 6, 1277976.
59. Sahoo, P. K., Mohapatra, S. K., & Wu, S. L. (2023). Healthcare big data analytics using cloud systems. Journal of Parallel and Distributed Computing, 172, 91–105.
60. Zeng, D., Cao, Z., & Wang, X. (2023). Predictive modeling for hospital readmission risk. IEEE Access, 11, 41231–41244.
61. Kumar, S., & Gupta, N. (2023). Explainable machine learning for healthcare predictions. Knowledge-Based Systems, 267, 110403.
62. Ali, F., Shah, B., & Khan, M. (2023). Intelligent predictive analytics in healthcare. Applied Soft Computing, 139, 110211.
63. Hassan, M., & Lee, S. (2023). Real-time healthcare data analytics using AI pipelines. Expert Systems, 40(8), e13254.
64. Aitha, A. R. (2023). Cloud-Native Big Data AI/ML Framework for Risk Intelligence and Fraud Control in Banking and Insurance Ecosystems. Available at SSRN 6157967.
65. Park, J., Kim, H., & Cho, Y. (2023). Unified big data architectures for clinical prediction. Journal of Biomedical Informatics, 145, 104465.
66. Zhao, L., Chen, H., & Li, T. (2023). Scalable predictive healthcare analytics using Spark. Cluster Computing, 26(4), 3119–3134.
67. Ahmed, R., & Noor, M. (2023). Federated predictive learning in healthcare systems. IEEE Transactions on Big Data, 9(3), 789–801.
68. Gottimukkala, V. R. R. (2020). Energy-Efficient Design Patterns for Large-Scale Banking Applications Deployed on AWS Cloud. power, 9(12).
69. Wang, H., & Xu, L. (2023). Big data-driven precision medicine. Briefings in Bioinformatics, 24(2), bbad041.
70. Patel, D., & Verma, R. (2023). Clinical event prediction using deep neural networks. Computers in Biology and Medicine, 157, 106742.
71. Singh, V., & Roy, S. (2023). Healthcare data lake architectures for predictive analytics. Data & Knowledge Engineering, 145, 102198.
72. Kolla, S. H. (2021). Rule-Based Automation for IT Service Management Workflows. Online Journal of Engineering Sciences, 1(1), 1-14.
73. Rao, P., & Menon, V. (2023). Risk prediction in healthcare using ensemble learning. Journal of Healthcare Engineering, 2023, 8876412.
74. Das, A., & Mishra, S. (2023). AI-enabled disease prediction using heterogeneous data. IEEE Transactions on Computational Social Systems, 10(5), 2244–2255.
75. Davuluri, P. N. AI-Augmented Sanctions Screening: Enhancing Accuracy and Latency in Real Time Compliance Systems.
76. Kumar, N., & Bansal, A. (2023). Predictive analytics for chronic disease management. Healthcare, 11(9), 1421.
77. Li, Y., Zhang, J., & Sun, M. (2023). Large-scale healthcare analytics with distributed systems. Information Processing & Management, 60(4), 103316.
78. Verma, S., & Tiwari, P. (2023). Big data governance in predictive healthcare. Journal of Information Science, 49(6), 1121–1135.
79. Mangalampalli, B. M. Generative AI Applications In Healthcare Data Mart Design And Optimization.
80. Singh, R., & Kaur, J. (2023). Data-driven predictive healthcare frameworks. Soft Computing, 27(14), 10211–10228.
81. Huang, W., Li, P., & Chen, Z. (2023). Multi-source healthcare data integration for prediction. Information Fusion, 92, 171–183.
82. Brown, C., & Taylor, M. (2023). Predictive healthcare analytics with interpretable AI. Artificial Intelligence in Medicine, 140, 102532.
83. Inala, R. Designing Scalable Technology Architectures for Customer Data in Group Insurance and Investment Platforms.
84. Mehta, S., & Rao, K. (2023). Scalable cloud-based healthcare analytics framework. Future Generation Computer Systems, 145, 86–99.
85. Dasgupta, P., & Sen, R. (2023). Unified predictive intelligence for healthcare big data ecosystems. Journal of Big Data, 10(1), 114.
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