Predicting Tumour Response With Radiomics and Machine Learning in MR-Guided Cervix Brachytherapy
Robert Bellis
Abstract:This study seeks to determine if radiomic features extracted from whole or part of the gross tumour volume of locally advanced cervical cancer (LACC) patients can be used to predict tumour response prior to brachytherapy treatment. 12 machine learning algorithms were tested with 5-fold cross validation using 1183 radiomic features extracted from 20 patients from T1, T2 and diffusion-weighted MR images. Recursive Feature Elimination was used to indicate the most predictive radiomic features of the most accurate… Show more
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