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https://github.com/prasanthyt/eb-dtwin

Dtwin is an AI-powered health management app that uses data from wearables like Fitbit to provide real-time health insights, early disease predictions, and personalized meal and fitness recommendations.
https://github.com/prasanthyt/eb-dtwin

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Dtwin is an AI-powered health management app that uses data from wearables like Fitbit to provide real-time health insights, early disease predictions, and personalized meal and fitness recommendations.

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README

          

# 🧠 Dtwin – All-in-One Health Management & Disease Prediction App

Dtwin is an AI-powered, full-stack health management application designed to deliver **personalized real-time health insights**, **early disease predictions**, and **custom meal and fitness recommendations**. Leveraging data from wearables like Fitbit and other real-time sources, Dtwin empowers users to take control of their health with AI-driven guidanceβ€”not generic advice.

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## πŸš€ Live Demo

πŸ”— **Live Web App**: [https://dtwin-health.app](https://dtwin.netlify.app/)

**NOTE:** This website is only mobile compatible.

πŸ”— **Backend API**: [https://api.dtwin-health.app](https://api.dtwin-health.app)

πŸ”— **DTwin APK**: [Download APK](https://drive.google.com/file/d/1lcvgrF0WuAXMbseI71wi1fbvrDyDSP5v/view?usp=sharing)

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## πŸ“Έ App Screenshots

| πŸ«€ Heart Analytics | πŸ€– Personalized Diet | πŸ”Ž Gut Analysis | |
|:---------------:|:----------------:|:----------------------:|:-:|
| ![](./public/screenshots/5.jpg) | ![](./public/screenshots/10.jpg) | ![](./public/screenshots/6.jpg) |

| πŸ“Š Main Dashboard | 🩺 Mental Wellness Chatbot | πŸ“ˆ Variable Data | |
|:---------------:|:----------------:|:----------------------:|:-:|
| ![](./public/screenshots/9.jpg) | ![](./public/screenshots/3.jpg) | ![](./public/screenshots/7.jpg) | |

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## 🧬 Features

- 🩺 **Disease Prediction**
Real-time risk prediction for:
- Heart Disease
- Diabetes
- Gut Health Disorders
- More conditions coming soon

- πŸ“Š **Real-Time Health Insights**
Get instant health feedback based on:
- Fitbit data
- Heart rate variability
- Step count, sleep patterns, calorie burn

- 🍽️ **Personalized Meal Plans**
Custom diet suggestions tailored to each user's:
- Blood sugar trends
- Activity level
- Gut microbiome profiles

- πŸƒβ€β™‚οΈ **Custom Exercise Recommendations**
Dynamic fitness plans based on:
- Energy expenditure
- Weight trends
- Recovery and fatigue scores

- πŸ“ˆ **Smart Analytics Dashboard**
Visualizations and predictions to help you make smarter decisions about your health.

---

## πŸ› οΈ Tech Stack

### πŸ”· Frontend
- React.js
- TailwindCSS
- Chart.js & D3.js (for visualizations)

### πŸ”Ά Backend
- Node.js
- Express.js
- REST API (with token-based authentication)
- MongoDB (for user data)

### πŸ§ͺ Machine Learning
- Python (Scikit-learn, TensorFlow)
- Trained on real-time + public datasets
- Served via FastAPI/Python microservices

### πŸ“± Mobile App
- Capacitor.js
- Android & iOS builds

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## πŸ“‚ Datasets Used

- **Heart Disease Prediction**: Garmin Real-Time Sensor Dataset
- **Diabetes Prediction**: IICMBC Clinical Dataset
- **Gut Health**: American Gut Project (AGP)

All models are trained with preprocessing pipelines and continuously updated using anonymized wearable data.

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## βš™οΈ Installation (Development)

### Prerequisites
- Node.js & npm
- Python 3.9+
- MongoDB running locally or Atlas DB

### Clone and Run

```bash
git clone https://github.com/yourusername/dtwin.git
cd dtwin

# Install frontend
cd client
npm install
npm start

# Install backend
cd ../server
npm install
npm run dev

# Run ML services
cd ../ml-service
pip install -r requirements.txt
uvicorn app:main --reload