AarogyaBytes is a web-based health assistant built to provide preliminary medical guidance through structured conversations.
The system helps users describe symptoms, answers follow-up questions, evaluates severity, and suggests an appropriate urgency level.
This project was developed as a hands-on learning exercise in building rule-based decision systems, interactive user interfaces, and client-side analytics.
The application guides users through a multi-step conversation flow:
- Initial symptom input
- Context-aware follow-up questions
- Severity assessment on a scale of 1–10
- Final assessment with urgency classification
Based on user inputs, the system determines whether the situation is low risk, moderate, urgent, or requires immediate medical attention.
https://aarogya-bytes.vercel.app/
- Structured symptom-based conversation flow
- Rule-based health condition inference
- Severity scoring and urgency classification
- Emergency symptom detection with escalation prompts
- Bilingual support (English and Hindi)
- PDF health report generation
- Analytics dashboard for tracking consultations and urgency trends
- The application is implemented entirely on the client side.
- Decision-making is based on weighted symptom matching and predefined rules.
- No external APIs or machine learning models are used.
- HTML
- CSS
- JavaScript
- jsPDF (for report generation)
AarogyaBytes/ ├── index.html ├── style.css ├── app.js ├── assets/ └── README.md
This project is intended for educational purposes only.
It does not provide medical diagnosis or replace professional medical consultation.
Ujwal Parashar
B.Tech Information Technology
Jaypee Institute of Information Technology, Noida
LinkedIn: https://linkedin.com/in/ujwal-parashar-3195a735a
GitHub: https://github.com/ujwal262006