Machine learning algorithms for outcome prediction in (chemo)radiotherapy: An empirical comparison of classifiers
Machine learning classification algorithms (classifiers) for prediction of treatment response are becoming more popular in radiotherapy literature. General Machine learning literature provides evidence in favor of some classifier families (random forest, support vector machine, gradient boosting) in terms of classification performance. The purpose of this study is to compare such classifiers specifically for (chemo)radiotherapy datasets and to estimate their average discriminative performance for radiation treatment outcome prediction.
Continue reading “Machine learning algorithms for outcome prediction in (chemo)radiotherapy: An empirical comparison of classifiers”READ MORE