Skip to main content

NaroNet: discovery of tumor microenvironment elements from multiplex images.

Project description

NaroNet: discovery of tumor microenvironment elements from multiplex imaging.

Trained only with patient-level labels, NaroNet quantifies the phenotypes, neighborhoods, and neighborhood interactions that have the highest influence on the predictive task. This is the python implementation as described in our paper.

Installation

For GPU support, it is crucial to install the specific versions of CUDA that are compatible with the version of Pytorch. For further information follow our github page

To install NaroNet:

pip install NaroNet

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

NaroNet-1.0.11.tar.gz (137.1 kB view details)

Uploaded Source

File details

Details for the file NaroNet-1.0.11.tar.gz.

File metadata

  • Download URL: NaroNet-1.0.11.tar.gz
  • Upload date:
  • Size: 137.1 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.8.0 pkginfo/1.8.2 readme-renderer/34.0 requests/2.27.1 requests-toolbelt/0.9.1 urllib3/1.26.8 tqdm/4.62.3 importlib-metadata/4.11.1 keyring/23.5.0 rfc3986/2.0.0 colorama/0.4.4 CPython/3.8.12

File hashes

Hashes for NaroNet-1.0.11.tar.gz
Algorithm Hash digest
SHA256 eccaa93201dcabcd4076c2ec6f5561c823de48afdb54824f20e893cbfaa364ea
MD5 bbeef5ecc0abbd0bfdf09121bc77ff1a
BLAKE2b-256 169177b3c4037bc70a229ab65bdb646c7091fd25b4495b4f5ad76ee059e1c225

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page