AI-Based Health Monitoring Systems Techniques, Applications and Challenges

In today’s fast-paced environment, routine health tracking plays a vital role in detecting chronic illnesses at an early stage. This work introduces HealthGuard, an AI-driven platform that leverages user-supplied health information to predict risks of diabetes, cardiovascular disease, and respiratory conditions. The system utilizes a Random Forest algorithm to ensure dependable and precise predictions. To make interaction more natural, it incorporates a chatbot capable of interpreting everyday language and offering immediate, relevant feedback. Additionally, an interactive dashboard records user history and visualizes prediction patterns, helping individuals stay informed and adopt preventive measures. This paper details the system’s design, development, and evaluation, emphasizing how predictive modeling combined with conversational AI can enable users to manage their health more effectively.

Publication Details

Journal
Iconic Research and Engineering Journals
Published
2025-12-04
DOI
https://doi.org/10.64388/irev9i5-1712279
Primary Topic
Artificial Intelligence in Healthcare
Type
article
Field-Weighted Citation Impact
0.00
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article

AI-Based Health Monitoring Systems Techniques, Applications and Challenges

Iconic Research and Engineering Journals
Artificial Intelligence in Healthcare
article

AI-Based Health Monitoring Systems Techniques, Applications and Challenges

article en

Abstract

In today’s fast-paced environment, routine health tracking plays a vital role in detecting chronic illnesses at an early stage. This work introduces HealthGuard, an AI-driven platform that leverages user-supplied health information to predict risks of diabetes, cardiovascular disease, and respiratory conditions. The system utilizes a Random Forest algorithm to ensure dependable and precise predictions. To make interaction more natural, it incorporates a chatbot capable of interpreting everyday language and offering immediate, relevant feedback. Additionally, an interactive dashboard records user history and visualizes prediction patterns, helping individuals stay informed and adopt preventive measures. This paper details the system’s design, development, and evaluation, emphasizing how predictive modeling combined with conversational AI can enable users to manage their health more effectively.

Iconic Research and Engineering JournalsVol. 9(5)
Openalex Percentile: Top 52%
Artificial Intelligence in Healthcare
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