Extended Data Fig. 8: Predictor importance plot for the random forest model averaged across the random initializations. | Nature Cancer

Extended Data Fig. 8: Predictor importance plot for the random forest model averaged across the random initializations.

From: A phase I/Ib trial and biological correlate analysis of neoadjuvant SBRT with single-dose durvalumab in HPV-unrelated locally advanced HNSCC

Extended Data Fig. 8: Predictor importance plot for the random forest model averaged across the random initializations.The alternative text for this image may have been generated using AI.

(A) Diagram depicting how the random forest model was trained. (B) Diagram depicting an example of how the model will determine if a patient responds to treatment. (C) Predictor importance is computed using the mean decrease in Gini index and plotted relative to the CD4+ effector T-cell importance, which had the maximum mean decrease in Gini index among the predictors. This figure was made with Python version 3.6.3 and Matplotlib version 3.2.2.

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