A submission for the Nightingale Challenge
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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:
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.txtClone the repo
git clone https://github.com/cswpy/ML4Healthcare.gitContributions 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!
- Fork the Project
- Create your Feature Branch (
git checkout -b feature/AmazingFeature) - Commit your Changes (
git commit -m 'Add some AmazingFeature') - Push to the Branch (
git push origin feature/AmazingFeature) - Open a Pull Request
Baraa Al Jorf - [email protected], Eddie Seung Hun Han - [email protected] , Philip Wang - [email protected]
Project Link: https://github.com/cswpy/ML4Healthcare