Predicting xerostomia after IMRT treatments: a data mining approach

AbstractXerostomia is one of the most frequent long term side-effects experienced by head-and-neck cancer patients undergoing radiation therapy, reducing drastically the quality-of-life of patients. In the present study, a prediction model for xerostomia after radiotherapy is proposed. Model construction was based on a dataset of 138 patients with head-and-neck cancer treated at the Portuguese Institute of Oncology of Coimbra (IPOCFG) with Intensity Modulated Radiation Therapy, using different data mining predictors. The models considered dosimetric information and patient specific features known prior to treatment to estimate which patients will experience xerostomia (G0 vs G1/G2 according to RTOG/EORTC). The quality of the classifiers was assessed by applying cross-validation procedures ...

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