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ML4Healthcare


Breast Cancer Stage Classification

A submission for the Nightingale Challenge
Learn more about the Challenge »

Report Bug · Request Feature

Table of Contents
  1. About The Project
  2. Getting Started
  3. Contributing
  4. Contact

About The Project

This repository contains code testing a variety of Machine Learning models on a a private dataset supplied through Nightingale. The repository contains a DenseNet model, a CLAM model, TransMIL, and a WENO dataloader

Github Repositories:

Built With

  • Jupyter

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Prerequisites

Before you can use this repository, you'll need to have the following installed:

  • Python (>= 3.6)
  • PyTorch (>= 1.7.0)
  • TorchVision (>= 0.8.0)
  • PyTorch Lightning (>= 1.2.0)
  • NumPy (>= 1.18.5)
  • Pandas (>= 1.1.4)
  • Matplotlib (>= 3.3.2)
  • Pillow (>= 7.2.0)
  • tqdm (>= 4.54.1)
  • slideflow[tf] (>= 0.4.0)
  • cucim (>= 0.19.0)
  • cupy-cuda11x (>= 9.2.0)

To install the required packages, you can use pip by running the following command in your notebook/terminal:

!pip install -r Nightingale/requirements.txt

Installation

Clone the repo

git clone https://github.com/cswpy/ML4Healthcare.git

Contributing

Contributions are what make the open source community such an amazing place to learn, inspire, and create. Any contributions or suggestions you make are greatly appreciated.

If you have a suggestion that would make this better, please fork the repo and create a pull request. You can also simply open an issue with the tag "enhancement". Don't forget to give the project a star! Thanks again!

  1. Fork the Project
  2. Create your Feature Branch (git checkout -b feature/AmazingFeature)
  3. Commit your Changes (git commit -m 'Add some AmazingFeature')
  4. Push to the Branch (git push origin feature/AmazingFeature)
  5. Open a Pull Request

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Contact

Baraa Al Jorf - [email protected], Eddie Seung Hun Han - [email protected] , Philip Wang - [email protected]

Project Link: https://github.com/cswpy/ML4Healthcare

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