ekstroem/CoOL: Causes of Outcome Learning

Implementing the computational phase of the Causes of Outcome Learning approach as described in Rieckmann, Dworzynski, Arras, Lapuschkin, Samek, Arah, Rod, Ekstrom. Causes of outcome learning: A causal inference-inspired machine learning approach to disentangling common combinations of potential causes of a health outcome. medRxiv (2020) <doi:10.1101/2020.12.10.20225243>. The optional 'ggtree' package can be obtained through Bioconductor.

Getting started

Package details

MaintainerAndreas Rieckmann <aric@sund.ku.dk>
URL https://bioconductor.org
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
ekstroem/CoOL documentation built on April 14, 2021, 4:23 a.m.