Doctrone is an intelligent medical assistant designed to help patients manage their medications, monitor treatment schedules, and receive personalized health advice from an AI-driven chatbot. It serves as a digital companion for individuals with chronic conditions or temporary illnesses — offering smart reminders, symptom analysis, and safe guidance based on the user’s personal medical profile.
Doctrone combines the power of AI conversation, medical data tracking, and multi-platform access to create a safe, intelligent, and always-available health companion. Users can chat directly with the AI to ask about side effects, dosage frequency, or symptoms. The system analyzes their stored medical data — such as prescriptions, age, blood type, and existing diagnoses — to generate context-aware, medically-relevant responses.
- AI Chatbot — Users can ask health-related questions about medications, symptoms, or conditions.
- Prescription Tracking — Keeps a history of prescribed drugs, dosages, and intake schedules.
- Medication Reminders — Notifies users when it’s time to take their medicine.
- Health Insights — The AI analyzes patient data to provide safe and personalized advice.
- Shared PostgreSQL Database — Both AI and Main API access the same data securely.
- Cross-Platform Access — Available on mobile (React Native) and web (React + Vite).
| Component | Technology | Description |
|---|---|---|
| Main API | C# (.NET) | Handles authentication, user management, and database communication. |
| AI Server | Python (Flask) | Processes chat requests, integrates with AI models, and fetches contextual data from the DB. |
| Database | PostgreSQL | Stores all user, prescription, and chat data. Shared between the APIs. |
| Platform | Stack | Purpose |
|---|---|---|
| Mobile App | React Native (TypeScript) | Main user interface for chat, reminders, and notifications. |
| Web App | React + Vite | It has the same functionality as the mobile app. |
The PostgreSQL schema includes 6 main entities:
| Table | Purpose |
|---|---|
| Users | Stores patient details (name, blood type, age, gender, diagnoses, credentials). |
| Prescriptions | Links users to their prescribed drugs, including dosage and intake schedule. |
| Drugs | Contains drug names and metadata for AI reference. |
| Chats | Manages conversation sessions between users and the AI. |
| Messages | Stores individual chat messages exchanged during each session. |
| Folders | Allows users to organize their chat sessions and prescriptions. |
- Node.js ≥ 18
- Python ≥ 3.10
- .NET SDK ≥ 8.0
- PostgreSQL ≥ 15
- npm / yarn
# Clone repository
git clone https://github.com/BolyarCoders/Doctrone.git
cd Src
# Install main API dependencies
cd Doctrone.Api/DoctrroneAPI
dotnet restore
dotnet run
# Install AI server dependencies
cd Doctrone.AI
pip install -r requirements.txt
python main.py
# Install web app dependencies
cd Doctrone.Website/react-app
npm install
npm run dev
# Install mobile app dependencies
cd Doctrone.MobileApp
# You need to install the expo-cli dependency and install their mobile app 'Expo Go' from Google Play Store & Apple Store
npm install -g expo-cli
npm install
npx expo start
# Follow the instructions given in the cli in order to run the Doctrone App on your phone
- User registers and logs into the mobile app (via .NET API).
- Every new user is asked about their medical prescriptions.
- The app retrieves the user’s prescriptions and chat history.
- User asks: “I feel dizzy after taking my pill, is that normal?”
- Mobile app sends the message to the AI server.
- AI queries the PostgreSQL DB for that user’s drugs and known side effects.
- AI replies with context-aware advice (“Mild dizziness is common for DrugX, but monitor your symptoms”).
- The response is stored in messages, maintaining the medical history thread.
| Layer | Technology |
|---|---|
| Backend | .NET (C#), Python (Flask) |
| Frontend | React, React Native, Vite |
| Database | PostgreSQL |
| ORM / Migrations | Entity Framework |
| AI Layer | Python (Gemini-2.5-flash model) |
| Hosting | Render / Expo Go / Supabase |
- Fork the repository
- Create a feature branch:
git checkout -b feature/chat-enhancement - Commit with a clear message:
git commit -m "Add health insight generation to AI responses" - Open a Pull Request to the dev branch.
Licensed under the MIT License — free for personal and commercial use. See LICENSE for details.
- Integration with wearable health devices.
- Doctor dashboard for remote patient monitoring.
- Voice-based AI interaction.
- Smart emergency alerts for dangerous symptoms.
- Advanced analytics for medication adherence.
