Web Driven Health Insights: An AI-Powered Recommendation System for Optimized Patient Care

DOI

10.2991/978-94-6463-852-3_11How to use a DOI?

Keywords

Health Recommender System; Artificial Intelligence; Personalized Medical Advice; Predictive Health Analytics; Machine Learning; Data Mining

Abstract

In order to manage huge amounts of medical data and provide personalized treatment for patients, the healthcare industry in the current digital era faces a growing need for intelligent technologies. The ground-breaking approach outlined in this paper aims to enhance medical decision-making by utilizing web-based health data and modern methods for machine learning. To provide individualized recommendations, such as treatment plans, medicine suggestions, and preventive measures, the recommended approach encompasses behaviour analysis, social activities, and health data about patients. The system’s main component, the Restricted Boltzmann Machine (RBM) and Convolutional Neural Networks (CNN), are deep learning algorithms which ensure accurate diagnosis and optimal patient care. TensorFlow and Python were implemented in the development of the system, while Fmeasure, accuracy, precision, and recall metrics were used to evaluate the system’s performance. In addition to illustrating the potential of AI-powered health recommender systems, this study highlights how crucial it is to guarantee data confidentiality, authenticity, and legal compliance in medical applications. The outcomes show how well the system operates to reduce healthcare expenditures while improving patient outcomes by making tailored, data-driven suggestions.

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  - Amaan Shaikh
AU  - Salim Shaikh
AU  - Tabassum Maktum
AU  - Vishal Gotarane
AU  - Shadulla Shaikh
PY  - 2025
DA  - 2025/10/07
TI  - Web Driven Health Insights: An AI-Powered Recommendation System for Optimized Patient Care
BT  - Proceedings of the MULTINOVA: First International Conference on Artificial Intelligence in Engineering, Healthcare and Sciences (ICAIEHS- 2025)
PB  - Atlantis Press
SP  - 162
EP  - 180
SN  - 1951-6851
UR  - https://doi.org/10.2991/978-94-6463-852-3_11
DO  - 10.2991/978-94-6463-852-3_11
ID  - Shaikh2025
ER  -