AI-Driven Predictive Models for Hospital Readmission: Reducing Healthcare Costs and Improving Patient Outcomes
Abstract
Hospital readmissions are a significant burden on healthcare systems. This paper investigates how artificial intelligence (AI) can predict patient readmissions and reduce their incidence through targeted interventions. We review various AI algorithms and their applications in analyzing patient data to identify those at high risk of readmission. Case studies from hospitals using these predictive models demonstrate their effectiveness in reducing readmission rates and associated costs. The paper also addresses challenges such as model accuracy, data integration, and ethical considerations, proposing strategies to enhance the adoption and impact of AI-driven predictive models in healthcare settings.
References
Narani, S. R., Ayyalasomayajula, M. M. T., & Chintala, S. (2018). Strategies For Migrating Large, Mission-Critical Database Workloads To The Cloud. Webology (ISSN: 1735-188X), 15(1).
Krutthika H. K. & A.R. Aswatha. (2020). FPGA-based design and architecture of network-on-chip router for efficient data propagation. IIOAB Journal, 11(S2), 7–25.
Krutthika H. K. & A.R. Aswatha (2020). Design of efficient FSM-based 3D network-on-chip architecture. International Journal of Engineering Trends and Technology, 68(10), 67–73. https://doi.org/10.14445/22315381/IJETT-V68I10P212
Krutthika H. K. & Rajashekhara R. (2019). Network-on-chip: A survey on router design and algorithms. International Journal of Recent Technology and Engineering, 7(6), 1687–1691. https://doi.org/10.35940/ijrte.F2131.037619
S. Ajay, et al., & Krutthika H. K. (2018). Source hotspot management in a mesh network-on-chip. 22nd International Symposium on VLSI Design and Test (VDAT-2018). https://doi.org/10.1007/978-981-13-5950-7_51
Adusumilli, S., Damancharla, H., & Metta, A. (2020). Artificial Intelligence-Driven Predictive Analytics for Educational Behavior Assessment. Transactions on Latest Trends in Artificial Intelligence, 1(1). Retrieved from https://www.ijsdcs.com/index.php/TLAI/article/view/638
Adusumilli, S., Damancharla, H., & Metta, A. (2020). Machine Learning Algorithms for Fraud Detection in Financial Transactions. International Journal of Sustainable Development in Computing Science, 2(1). Retrieved from https://www.ijsdcs.com/index.php/ijsdcs/article/view/639
Adusumilli, S. B. K., Damancharla, H., & Metta, A. R. (2020). Leveraging AI for Real-Time Sentiment Analysis in Social Media Networks. International Numeric Journal of Machine Learning and Robots, 4(4).
