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Saksham,
Surbhi Mishra,
Shobha Rawal,
- Researcher, Department of Computer Science and Engineering (CSE), Greater Noida Institute of Technology (GNIT), Greater Noida, Uttar Pradesh, India
- Researcher, Department of Computer Science and Engineering (CSE), Greater Noida Institute of Technology (GNIT), Greater Noida, Uttar Pradesh, India
- Researcher, Department of Computer Science and Engineering (CSE), Greater Noida Institute of Technology (GNIT), Greater Noida, Uttar Pradesh, India
Abstract
The AI-Based Dental Care Solution System is a web-based healthcare application developed using the MERN stack (MongoDB, Express. js, React.js, and Node.js) and integrated with Artificial Intelligence techniques to support early and accessible dental self-assessment. The system assists users in preliminary dental consultation by collecting symptoms such as tooth pain, sensitivity, swelling, bleeding gums, and bad breath through both structured forms and a conversational chatbot interface. Using Natural Language Processing (NLP) and supervised machine learning, it analyzes the input to predict common dental conditions including cavities, gingivitis, periodontitis, and tooth abscess, and presents the output in an interpretable and user-friendly format. Based on the prediction, the system provides basic medication suggestions, evidence-informed home care measures, and preventive care guidance drawn from a controlled dental knowledge base reviewed by a dental practitioner. The application features a responsive user interface, secure backend processing, structured data management, and a modular AI engine that can be updated independently of the core application. It also includes safety measures such as visible medical disclaimers, confidence scores, and urgency indicators to guide users on when professional dental care is required rather than selfmanagement. The main objective of this project is to promote early identification of dental issues, enhance public dental health awareness, and reduce unnecessary clinical visits through intelligent, scalable, and accessible digital support while still respecting clinical boundaries and ethical considerations.
Keywords: Artificial Intelligence, Dental Care, NLP, Machine Learning, MERN Stack, Symptom Analysis, Healthcare Chatbot, Disease Prediction, Preventive Den- tistry
[This article belongs to Research and Reviews: A Journal of Dentistry ]
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Research and Reviews: A Journal of Dentistry
| Volume | 17 | |
| Issue | 02 | |
| Received | 06/07/2026 | |
| Accepted | 17/07/2026 | |
| Published | 24/08/2026 | |
| Publication Time | 49 Days |