N INTELLIGENT CHATBOT FOR PUBLIC HEALTH AWARENESS USING ARTIFICIAL INTELLIGENCE

Main Article Content

Dr. Jyoti Kaushal

Abstract

: The problem is that public health awareness still lags in underserved areas. It seems hard to ignore how gaps in access affect real outcomes. And we built an AI chatbot that delivers accurate health info and guidance in English and Hindi. The system mixes rule-based logic with machine learning to interpret user questions. It draws from verified FAQs and trusted medical texts for its knowledge base. Structure includes language models, data pipelines, and evaluation tracks for comprehension and engagement. Our work combines evidence-based content with modern AI tools. This improves reach for rural users without sacrificing accuracy or privacy. Ethical concerns like data safety and truthfulness are addressed directly. The roadmap outlines steps toward a scalable, multilingual health assistant.
Keywords: AI chatbot, public health, health awareness, NLP, multilingual health, rural healthcare, conversational agent, digital health

Article Details

Section

Articles

Author Biography

Dr. Jyoti Kaushal

Associate Professor, CSE
Geetanjali Institute of Technical Studies
Udaipur, India

References

Core AI & Healthcare Chatbot Studies

[1] Kurniawan, M. H., et al. (2024): A systematic review of artificial intelligence-powered chatbot intervention for managing chronic illness. Journal of Advanced Nursing.

[2] Laranjo, L., et al. (2018): Conversational agents in healthcare: A systematic review. Journal of the American Medical Informatics Association.

[3] Feng, S., Li, X., & Wake, A. N. (2026):

Engaging AI-based chatbots in digital health- A systematic review. PLOS Digital Health.

Public Health & Chatbot Applications

[4] Wilson, M., & Marasoiu, M. (2022): The development and use of chatbots in public health- A scoping review. Journal of Medical Internet Research.

[5] Aggarwal, A., et al. (2023): Artificial intelligence-based chatbots for promoting health behavioral changes. Journal of Medical Internet Research.

AI Models & NLP (for methodology support)

[6] Devlin, J., et al. (2019): BERT: Pre-training of deep bidirectional transformers for language understanding. NAACL Conference

[7] Brown, T., et al. (2020): Language models are few-shot learners (GPT-3). NeurIPS

[8] Vaswani, A., et al. (2017): Attention is all you need. NeurIPS

AI Chatbots in Public Health Systems

[9] Xiao, Z., et al. (2023): Powering an AI chatbot with expert sourcing to support credible health information access.

[10] Chen, C., & Stadler, T. (2023): GenSpectrum Chat: Data exploration in public health using LLMs.

Chatbot Effectiveness & Trust Studies

[11] Nov, O., et al. (2023): Putting ChatGPT’s medical advice to the test.

[12] Sehgal, N., et al. (2025).

Chatbots and vaccine intention: A randomized study.