AI-Driven Prediction of Hospitalization and Healthcare Cost Estimation

DOI

10.2991/978-94-6463-866-0_12How to use a DOI?

Keywords

Machine Learning; Socioeconomics; Healthcare Cost Estimation

Abstract

The healthcare sector is increasingly utilizing drone technology and artificial intelligence (AI) to enhance disease prediction, manage medical supplies, and deliver free healthcare services targeting major causes of death such as heart disease, stroke, and diabetes. These chronic conditions pose serious challenges to patient health and system efficiency. AI-driven solutions analyze diverse medical data to anticipate disease progression and recurrence, while also suggesting appropriate medications, hospital appointments, and specialist consultations based on individual patient profiles. This personalized approach improves clinical outcomes, optimizes resource allocation, and streamlines patient evaluation. In emergency care, AI can predict admissions, length of stay, and treatment costs by assessing factors such as socioeconomic status, disease severity, and physiological indicators like heart rate. Machine learning algorithms enable healthcare providers to make data-informed decisions, improving care planning and patient management. Additionally, AI supports hospital prescribing practices by offering tailored recommendations that contribute to more comprehensive patient care. By incorporating these predictive technologies into the healthcare delivery system, providers can reduce operational costs, boost efficiency, and elevate patient satisfaction. As a result, AI is shaping a dynamic and responsive healthcare environment that better addresses patient needs while supporting healthcare professionals in delivering timely and effective interventions.

Copyright

© 2025 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - S. K. M. Siddiq
AU  - S. Guru Giridhar Kumar
AU  - S. Suchitra
PY  - 2025
DA  - 2025/10/31
TI  - AI-Driven Prediction of Hospitalization and Healthcare Cost Estimation
BT  - Proceedings of the International Conference on Intelligent Systems and Digital Transformation (ICISD 2025)
PB  - Atlantis Press
SP  - 115
EP  - 122
SN  - 2589-4919
UR  - https://doi.org/10.2991/978-94-6463-866-0_12
DO  - 10.2991/978-94-6463-866-0_12
ID  - Siddiq2025
ER  -