Copyright © 2026 Authors retain the copyright of this article. This article is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
@article{197958,
author = {Pratiksha gabhane and Pratiksha Chaudhary and Sanjana Gajbhiye and Puja Bhoyar},
title = {AI-Based Smart Health Monitoring with Live Data Analysis},
journal = {International Journal of Innovative Research in Technology},
year = {2026},
volume = {12},
number = {11},
pages = {12105-12107},
issn = {2349-6002},
url = {https://ijirt.org/article?manuscript=197958},
abstract = {This paper presents an AI-Based Smart Health Monitoring System designed to analyze patient health data and provide intelligent insights. The system uses multiple machine learning algorithms such as Isolation Forest, Random Forest, Logistic Regression, and Decision Tree to monitor vital parameters like heart rate, temperature, and oxygen levels. It provides real-time analysis, risk prediction, and patient-friendly advice through an interactive graphical user interface. The system also includes a query-based interaction module that allows patients to ask health-related questions. This approach enhances early detection of health risks and improves decision-making in healthcare systems.},
keywords = {Artificial Intelligence, Health Monitoring, Machine Learning, Data Analysis, Patient Care.},
month = {April},
}
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