Helping patients reach the right specialist faster.
Doctor AI Assistant is a live, end-to-end web application that converts plain-language symptom descriptions into a practical medical specialty recommendation. It solves a simple but costly user problem: patients know what they feel, but often do not know which doctor they should see first.
The Problem
Patients frequently lose time and money by choosing the wrong specialist for their first consultation. This is especially common when symptoms are vague, overlap multiple conditions, or appear outside normal clinic hours.
- Unclear symptoms lead to trial-and-error appointments.
- Care is delayed when the first doctor is not the right fit.
- Many users need fast guidance before speaking to a hospital or clinic.
The Solution
The app offers a conversational triage experience. Users describe symptoms in natural language, the backend applies structured prompting with OpenAI, and the system recommends the most suitable doctor category.
- Simple chat-based symptom capture.
- Backend prompt constraints to keep responses focused.
- Safe fallback to General Physician when certainty is low.
Demo Video
This walkthrough shows the live product flow, including symptom entry and specialist recommendation.
What Judges Can Evaluate Quickly
- Clarity: the problem statement is easy to understand in under 30 seconds.
- Functionality: the product is live and produces specialty recommendations from real symptom input.
- Product thinking: the flow is simple, useful, and positioned for real-world extension.
- Technical completeness: frontend, backend, AI integration, and deployment are all working together.
Suggested Test Prompts
- "I have chest pain and shortness of breath."
- "I have a persistent skin rash and itching for two weeks."
- "I have frequent headaches, dizziness, and blurred vision."
- "I have ear pain and reduced hearing in one ear."
Evaluation Flow
- Open the live app and enter one of the sample symptom prompts.
- Observe the chat-based interaction and the resulting specialist recommendation.
- Review the demo video for a concise end-to-end walkthrough.
- Inspect the repository to verify the implementation is organized and deployable.
- Assess future scalability across telemedicine intake, hospital routing, and multilingual support.
Frontend
HTML, CSS, and JavaScript power a responsive chat interface designed for fast symptom capture and low friction during demos.
Backend
Node.js and Express handle API requests and keep the OpenAI key on the server side rather than exposing it in the browser.
AI Layer
OpenAI is used with constrained prompting to map symptom descriptions to an appropriate medical specialty and avoid vague output.
Impact
Doctor AI Assistant demonstrates a practical application of AI in healthcare access. Instead of replacing medical professionals, it improves the first routing decision and reduces uncertainty for patients.
Next Steps
The current version is intentionally lightweight, but the roadmap is strong: urgency scoring, appointment routing, multilingual interaction, and clinic-specific specialist networks.
This project is an informational triage assistant, not a diagnostic or treatment system.