Chowell2022 - Random Forest model to predict efficacy of immune checkpoint blockade across multiple cancer patient cohorts

This is a Random Forest algorithm-based machine learning model called RF16, which incorporates a total of 16 genomic, molecular, demographic, and clinical features to predict the immunotherapy response for a patient. The model assigns a value of 0 for NonResponder and 1 for Responder. Please be aware that the column names in the GitHub code and the downloaded dataset from the publication may vary. Users are advised to make minor adjustments to either the code or the dataset to ensure compatibility. The curated version of the model has modified the column names in the training code to align with the dataset.

GitHub repository: https://github.com/CCF-ChanLab/MSK-IMPACT-IO