vaishnaviyrathod/stream-cancer-predict

Stream-Cancer-Predict is a Streamlit app for predicting breast mass malignancy using cell nuclei data. It features real-time updates, interactive sliders, and radar chart visualization for intuitive analysis

stream-cancer-predict

Stream-Cancer-Predict is a Streamlit app for predicting breast mass malignancy using cell nuclei data. It features real-time updates, interactive sliders, and radar chart visualization for intuitive analysis Certainly! Here's the text you can use for your README.md file:

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Stream-Cancer-Predict

Stream-Cancer-Predict is a Streamlit web application designed for predicting breast mass malignancy based on cell nuclei measurements. Users can interactively adjust input values via sliders, visualize data with radar charts, and receive real-time predictions from a pre-trained machine learning model.

Features

• Interactive Sliders: Adjust cell nuclei measurements.
• Real-time Updates: See predictions update dynamically.
• Radar Chart Visualization: Visual representation of input data.
• Pre-trained Model: Uses a trained model for accurate predictions.

Getting Started

1. Clone the repository:

   git clone https://github.com/your-username/stream-cancer-predict.git
   cd stream-cancer-predict

2. Install dependencies:

   pip install -r requirements.txt

3. Run the application:

   streamlit run main.py

4. Open http://localhost:8501 in your browser to use the app.

Usage

1. Adjust sliders to change cell nuclei measurements.
2. View real-time updates in the radar chart.
3. Receive predictions and probabilities instantly.

Model Training

For details on model training and dataset used, see model_training.ipynb.

Contributing

Contributions are welcome! Please fork the repository and submit pull requests.

License

This project is licensed under the MIT License. See the LICENSE file for details.