Skip to content

AI model source for detecting CDH1 bi-allelic mutations in breast pathology samples

License

Notifications You must be signed in to change notification settings

Paige-AI/cdh1-cancer-res

Repository files navigation

CDH1 Cancer Research

License: CC BY-NC-ND 4.0

ADD LINK TO PAPER.

Reproducing Inference

Requirements

  • Python 3.8 or later
  • CPU

Setup

After cloning the repository to your local machine, install the code in editable mode from the repositories root directory cdh1-cancer-res/ by executing pip install -e .

Test the setup

To test that the installation works, script a single aggregator model. A successful test should return Created torchscripted checkpoint at <PATH>. To run the setup test, execute the following command: python -m cdh1_cancer_res.model

Run the demo prediction

    1. Script the ensemble model:
    • python -m cdh1_cancer_res.script_ensemble
    • This will create the torchscripted ensemble model we will require to run our demo predictions.
    1. Predict the CDH1 on the provided demo embeddings using the torchscripted ensemble model:
    • python -m cdh1_cancer_res.predict
    • The prediction step should print our the ground truth values, the model's continuous and binarized prediction.

Paige.AI CDH1 Cancer Research (c) by Paige.AI

Paige.AI CDH1 Cancer Research is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

You should have received a copy of the license along with this work. If not, see http://creativecommons.org/licenses/by-nc-nd/4.0/.

About

AI model source for detecting CDH1 bi-allelic mutations in breast pathology samples

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages