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---
license: mit
sdk: gradio
---
---
license: mit
---
# 🧠 Disease Symptom Prediction AI
AI-powered tool that predicts possible diseases based on symptoms using a trained machine learning model and provides chatbot-style suggestions.
---
## 📁 Project Structure
```
disease-symptom-prediction/
├── data/ # Excel dataset (not uploaded)
│ └── README.md # Instructions for downloading from Kaggle
│
├── src/ # Source code
│ ├── data_preprocessing.py # Cleans & prepares dataset
│ ├── model.py # Trains and saves the ML model
│ ├── predict.py # Predicts disease from symptoms
│ └── chatbot.py # Symptom-checker chatbot logic
│
├── app/ # App interface
│ └── gradio_app.py # Gradio-based web UI
│
├── models/ # Trained model files
│ └── rf_model.pkl
│
├── notebooks/ # Jupyter notebooks for analysis
│ ├── 1_data_exploration.ipynb
│ ├── 2_preprocessing_test.ipynb
│ └── 3_model_testing.ipynb
│
├── requirements.txt # Python dependencies
├── .gitignore
└── README.md
```
---
## ⚙️ Installation
### 1. Clone the repository
```bash
git clone https://github.com/your-username/disease-symptom-prediction.git
cd disease-symptom-prediction
```
### 2. Create virtual environment (optional but recommended)
```bash
python -m venv venv
source venv/bin/activate # On Windows: venv\Scripts\activate
```
### 3. Install dependencies
```bash
pip install -r requirements.txt
```
---
## 🚀 Run the App
```bash
python app/gradio_app.py
```
The app will start locally and you can open it in your browser at `http://localhost:7860`.
---
## 🤖 Features
- ✅ Predict disease from symptoms
- 🧠 Trained on structured healthcare dataset
- 💬 Chatbot-style health advice
- 🖥️ User-friendly Gradio interface
---
<details>
<summary>📦 Dataset Note (Click to expand)</summary>
We use a healthcare dataset available on [Kaggle](https://www.kaggle.com/). Due to licensing, it is not uploaded in this repo. Please download it manually and place it in the `data/` directory.
</details>
---
## 🪪 License
This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.
---
## 🙏 Credits
Created by [Mate](https://github.com/your-username) — feel free to fork, star, or contribute.
--- |