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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM63538
Volume:
10 |
5 |
May 2026
Pages:
1-3
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
Masters of Computer Applications
Bapuji Institute of Engineering and technology
Masters of Computer Applications
Bapuji Institute of Engineering and technology
The rapid growth of digital healthcare technologies has created opportunities for improving public health awareness through intelligent systems. However, many individuals still struggle to access reliable and timely health information, leading to misinformation and delayed preventive actions. Traditional health information systems are mostly static and lack interactive communication capabilities. This research proposes an AI-Driven Public Health Chatbot for Disease Awareness, an intelligent system designed to provide real-time health guidance using Natural Language Processing (NLP) and machine learning techniques. The chatbot enables users to ask disease-related questions, receive preventive recommendations, and obtain awareness information through conversational interaction. The system integrates a disease knowledge base, NLP-based intent recognition, and AI-driven response generation to ensure accurate and user-friendly communication. Implemented as a web-based platform, the chatbot real-time responses, and scalable deployment across devices. Experimental observations demonstrate improved accessibility to health information and enhanced user engagement.
KEYWORDS
The AI-Driven Public Health Chatbot for Disease Awareness demonstrates the potential of artificial intelligence in improving healthcare communication. By integrating NLP and machine learning, the system delivers accurate and accessible health information to users through conversational interaction. The project successfully reduces dependency on static health awareness methods and promotes proactive disease prevention. It provides a scalable and intelligent platform that can be extended with advanced features such as real-time disease tracking and multilingual voice support.
[1] Arnold V. Lim W. A. & Powell L. (2024). Chatbots and COVID-19: Taking stock of the lessons learned.Journal of Medical Internet Research. [2] Choi E. et al. (2020). Doctor AI:Predicting clinical events via recurrent neural networks.Lee J. & Lee T. (2021). The indisease diagnosis. International Journal of Medical Informatics 151 104482. [3] Lim W. A. et al. (2024). Generalcharacteristics and design taxonomy of chatbots for COVID-19: A systematic review. Journal of Medical Internet Research. [4] Patel V. L. & A. W. (2019). The role of artificial intelligence in clinical decisionmaking.
Publication Date
5/20/2026
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
Funding Information
No funding information available for this research.
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