Timo M Deist, Frank J W M Dankers, Gilmer Valdes, Robin Wijsman, I-Chow Hsu, Cary Oberije, Tim Lustberg, Johan van Soest, Frank Hoebers, Arthur Jochems, Issam El Naqa, Leonard Wee, Olivier Morin, David R Raleigh, Wouter Bots, Johannes H Kaanders, José Belderbos, Margriet Kwint, Timothy Solberg, René Monshouwer, Johan Bussink, Andre Dekker, Philippe Lambin
PURPOSE: 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...
July 2018: Medical Physics