https://github.com/bhklab/hpv-predict

Predicting HPV status in head and neck cancer (HNC) patients from medical imaging.

https://github.com/bhklab/hpv-predict

Science Score: 26.0%

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    Low similarity (9.2%) to scientific vocabulary
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Repository

Predicting HPV status in head and neck cancer (HNC) patients from medical imaging.

Basic Info
Statistics
  • Stars: 0
  • Watchers: 0
  • Forks: 0
  • Open Issues: 1
  • Releases: 1
Created about 1 year ago · Last pushed about 1 year ago
Metadata Files
Readme

docs/README.md

HPV Predict

Authors: Katy Scott, Reza Reiazi

Contact: bhklab.katyscott@gmail.com

Description: Predicting HPV status in head and neck cancer (HNC) patients from medical imaging. Code recovered from HPC4Health and uploaded to bhklab as back-up.

Original code is dated 2021-08-29.

!!! warning
NO ENVIRONMENT SETUP HAS BEEN DONE FOR THIS PROJECT. A Dockerfile is available in the docker/ directory and was used on the H4H compute cluster but has not been adapted.


Owner

  • Name: BHKLAB
  • Login: bhklab
  • Kind: organization
  • Location: Toronto, Ontario, Canada

The Haibe-Kains Laboratory @ Princess Margaret Cancer Centre

GitHub Events

Total
  • Release event: 1
  • Push event: 2
  • Pull request event: 1
  • Create event: 5
Last Year
  • Release event: 1
  • Push event: 2
  • Pull request event: 1
  • Create event: 5

Dependencies

.github/workflows/conventional-pr.yaml actions
  • amannn/action-semantic-pull-request v5.0.2 composite
  • peter-evans/create-or-update-comment v4 composite
.github/workflows/data-audit.yaml actions
  • actions/checkout v3 composite
  • actions/github-script v6 composite
.github/workflows/publish-docs.yaml actions
  • actions/checkout v3 composite
  • prefix-dev/setup-pixi v0.8.1 composite
.github/workflows/release-please.yaml actions
  • GoogleCloudPlatform/release-please-action v4 composite
  • actions/checkout v4.2.0 composite
docker/convert_caffe/Dockerfile docker
  • caffe2ai/caffe2 latest build
docker/hpv_status/Dockerfile docker
  • tensorflow/tensorflow 2.0.1-gpu-py3 build