Leveraging Computational Methods for Predictive Analytics in Healthcare: From Big Data to Personalized Medicine
Abstract
Predictive analytics, powered by advanced computational methods, is transforming the healthcare sector by enabling personalized medicine and proactive patient care. This paper delves into the role of computational techniques, including machine learning, data mining, and statistical modeling, in predictive analytics for healthcare. We discuss the utilization of big data from electronic health records (EHRs), genomics, and wearable devices to develop predictive models for disease risk assessment, patient stratification, and treatment response prediction. Case studies demonstrating the successful implementation of these models in chronic disease management, oncology, and emergency care are presented. Furthermore, the paper addresses the challenges of data integration, model interpretability, and regulatory compliance. The insights provided emphasize the transformative impact of predictive analytics on enhancing healthcare delivery and patient outcomes.
References
Augustin, A., Yi, J., Clausen, T., & Townsley, W. M. (2016). A study of LoRa: Long range & low power networks for the internet of things. Sensors, 16(9), 1466. https://doi.org/10.3390/s16091466
Centenaro, M., Vangelista, L., Zanella, A., & Zorzi, M. (2016). Long-range communications in unlicensed bands: The rising stars in the IoT and smart city scenarios. IEEE Wireless Communications, 23(5), 60-67. https://doi.org/10.1109/MWC.2016.7721743
Mekki, K., Bajic, E., Chaxel, F., & Meyer, F. (2019). A comparative study of LPWAN technologies for large-scale IoT deployment. ICT Express, 5(1), 1-7. https://doi.org/10.1016/j.icte.2017.12.005
Adelantado, F., Vilajosana, X., Tuset-Peiró, P., Martínez, B., Melia-Segui, J., & Watteyne, T. (2017). Understanding the limits of LoRaWAN. IEEE Communications Magazine, 55(9), 34-40. https://doi.org/10.1109/MCOM.2017.1600613
Bor, M. C., Vidler, J. E., & Roedig, U. (2016). LoRa for the Internet of Things. Proceedings of the 2016 International Conference on Embedded Wireless Systems and Networks (EWSN), 361-366.
Bacco, M., Barsocchi, P., Ferro, E., Gotta, A., & Pelliccia, R. (2017). Experimental assessment of the coexistence of LoRaWAN and IEEE 802.11ah networks for IoT applications. IEEE Access, 6, 19720-19729. https://doi.org/10.1109/ACCESS.2018.2812819
Croce, D., Marano, S., Di Benedetto, M. G., & Graziosi, F. (2018). Impact of spreading factor imperfections in LoRa communications. IEEE Transactions on Wireless Communications, 19(8), 5468-5479. https://doi.org/10.1109/TWC.2018.2829709
Saari, M., Valta, J., Kalliola, K., & Raitoharju, J. (2020). Enhancing LoRaWAN scalability through interference mitigation. IEEE Internet of Things Journal, 7(8), 6822-6830. https://doi.org/10.1109/JIOT.2020.2974016
Reynders, B., Meert, W., & Pollin, S. (2017). Power and spreading factor control in low power wide area networks. Proceedings of the 2017 IEEE International Conference on Communications (ICC), 1-6. https://doi.org/10.1109/ICC.2017.7996508
Yousuf, S., Sharif, M., Tanveer, W. H., & Anwar, S. (2018). A comprehensive survey on the applications of LoRa technology in the Internet of Things (IoT). Proceedings of the 2018 International Conference on Computing, Electronics & Communications Engineering (iCCECE), 21-26. https://doi.org/10.1109/iCCECOME.2018.8658717
Gonaygunta, H. (2023). Factors Influencing the Adoption of Machine Learning Algorithms to Detect Cyber Threats in the Banking Industry. University of the Cumberlands.
Gonaygunta, H., Meduri, S. S., Podicheti, S., & Nadella, G. S. (2023). The Impact of Virtual Reality on Social Interaction and Relationship via Statistical Analysis. International Journal of Machine Learning for Sustainable Development, 5(2), 1-20
Gonaygunta, H., Maturi, M. H., Nadella, G. S., Meduri, K., & Satish, S. (2024). Quantum Machine Learning: Exploring Quantum Algorithms for Enhancing Deep Learning Models. International Journal of Advanced Engineering Research and Science, 11(05).
Gonaygunta, H., Nadella, G. S., Pawar, P. P., & Kumar, D. (2024, May). Enhancing Cybersecurity: The Development of a Flexible Deep Learning Model for Enhanced Anomaly Detection. In 2024 Systems and Information Engineering Design Symposium (SIEDS) (pp. 79-84). IEEE.
Meduri, K. (2024). Cybersecurity threats in banking: Unsupervised fraud detection analysis. International Journal of Science and Research Archive, 11(2), 915-925.
Meduri, K., Nadella, G. S., Gonaygunta, H., & Meduri, S. S. (2023). Developing a Fog Computing-based AI Framework for Real-time Traffic Management and Optimization. International Journal of Sustainable Development in Computing Science, 5(4), 1-24.
Nadella, G. S., Gonaygunta, H., Meduri, K., & Satish, S. (2023). Adversarial Attacks on Deep Neural Network: Developing Robust Models Against Evasion Technique. Transactions on Latest Trends in Artificial Intelligence, 4(4).
Nadella, G. S., Meduri, S. S., Gonaygunta, H., & Podicheti, S. (2023). Understanding the Role of Social Influence on Consumer Trust in Adopting AI Tools. International Journal of Sustainable Development in Computing Science, 5(2), 1-18.
Nadella, G. S., Satish, S., Meduri, K., & Meduri, S. S. (2023). A Systematic Literature Review of Advancements, Challenges and Future Directions of AI And ML in Healthcare. International Journal of Machine Learning for Sustainable Development, 5(3), 115-130.
Nadella, G. S. (2023). Validating the Overall Impact of IS on Educators in US High Schools Using IS-Impact Model–A Quantitative PLS-SEM Approach. University of the Cumberlands.
Nadella, G. S., & Pillai, S. E. V. S. (2024, March). Examining the Indirect Impact of Information and System Quality on the Overall Educators' Use of E-Learning Tools: A PLS-SEM Analysis. In SoutheastCon 2024 (pp. 360-366). IEEE.
Kondru, V. L. P. (2017). Interconnected Pathologies: Exploring the Relationship Between Rheumatoid Arthritis and Periodontitis. Transactions on Latest Trends in Health Sector, 9(9).
Kondru, V. (2017). The Impact of Hypophosphatemia on Chondrocyte Fate (Doctoral dissertation).
Kondru, V. L. P. (2016). Exploring the Interplay of Food Habits, Genetics, and Environment: Implications for Dental and General Health. International Journal of AI-Assisted Medicine , 3(3), 1-20.
Kondru, V. L. P. (2016). Smoking, Alcohol Consumption, and Periodontitis: A Comprehensive Review of the Association and Implications for Oral Health. Transactions on Latest Trends in Health Sector, 8(8).
Kondru, V. L. P. (2016). Addressing the Disparities: The Burden of Dental Health in Low-Income Countries vs. Developed Countries and its Impact on Government Resources and Societal Well-being. International Journal of Medical Informatics and AI, 3(3), 1-17.
Kondru, V. L. P. (2015). Comparative Analysis of Healthcare Systems: A Study of India and the United States. Transactions on Latest Trends in Health Sector, 7(7).
Kondru, V. L. P. (2015). Electronic Health Care Records-Boon To Industry. International Journal of Medical Informatics and AI, 2(2), 1-18.
Kondru, V. L. P. (2014). Understanding Fluorosis: Implications for Dental and General Health. Transactions on Latest Trends in Health Sector, 6(6).
Kondru, V. L. P. (2014). Comparative Analysis of Oral Cancer Prevalence: Rural vs. Urban India and India vs. Developed . Journal of Healthcare Data Science and AI , 1(1), 1-20.
Kondru, V. L. P. (2014). Understanding Fluorosis: Implications for Dental and General Health. Transactions on Latest Trends in Health Sector, 6(6).
Kondru, V. L. P. (2014). Disparities in Dental Health Education: A Comparative Study of Rural and Urban Populations in India. International Journal of Medical Informatics and AI, 1(1), 1-17.
Kondru, V. L. P. (2014). A Review of the Association between Smoking, Alcohol Consumption, and Oral Cancer Risk. Journal of Healthcare AI and ML , 1(1), 1-18. https://journalpublication.wrcouncil.org/index.php/JHAM/article/view/6
Yadav, H. (2023). Securing and Enhancing Efficiency in IoT for Healthcare Through Sensor Networks and Data Management. International Journal of Sustainable Development Through AI, ML and IoT, 2(2), 1-9.
Yadav, H. (2023). Enhanced Security, Privacy, and Data Integrity in IoT Through Blockchain Integration. International Journal of Sustainable Development in Computing Science, 5(4), 1-10.
Yadav, H. (2023). Advancements in LoRaWAN Technology: Scalability and Energy Efficiency for IoT Applications. International Numeric Journal of Machine Learning and Robots, 7(7), 1-9.
Yadav, H. (2024). Scalable ETL pipelines for aggregating and manipulating IoT data for customer analytics and machine learning. International Journal of Creative Research In Computer Technology and Design, 6(6), 1-30.
Yadav, H. (2024). Anomaly detection using Machine Learning for temperature/humidity/leak detection IoT. International Transactions in Artificial Intelligence, 8(8), 1-18.
Yadav, H. (2024). Structuring SQL/NoSQL databases for IoT data. International Journal of Machine Learning and Artificial Intelligence, 5(5), 1-12.
