A machine-learning-based prediction model of fistula formation after interstitial brachytherapy for locally advanced gynecological malignancies.
Journal:
Brachytherapy
PMID:
31103434
Abstract
PURPOSE: External beam radiotherapy combined with interstitial brachytherapy is commonly used to treat patients with bulky, advanced gynecologic cancer. However, the high radiation dose needed to control the tumor may result in fistula development. There is a clinical need to identify patients at high risk for fistula formation such that treatment may be managed to prevent this toxic side effect. This work aims to develop a fistula prediction model framework using machine learning based on patient, tumor, and treatment features.