Machine Learning Analysis of Image Data Based on Detailed MR Image Reports for Nasopharyngeal Carcinoma Prognosis

Figure 1

Flow chart of feature selection used in this study. First step: feature selection to reduce features. Second step: AutoML is run. AutoML performs hyperparameter search (parameters such as tree and depth in the flow chart are representative examples) over a variety of H2O algorithms to deliver the best model. The hyperparameters of AutoML supported by grid search are listed in Supplementary Material 1. Abbreviations: mRMR, minimum redundancy maximum correlation; GLM, generalized linear model; XRT, extreme random tree; GBM, gradient boosting machine; RF, random forest; DL, deep learning.