[A Study on Radiation Dermatitis Grading Support System Based on Deep Learning by Hybrid Generation Method].
Journal:
Nihon Hoshasen Gijutsu Gakkai zasshi
PMID:
34421066
Abstract
PURPOSE: Radiation dermatitis is one of the most common adverse events in patients undergoing radiotherapy. However, the objective evaluation of this condition is difficult to provide because the clinical evaluation of radiation dermatitis is made by visual assessment based on Common Terminology Criteria for Adverse Events (CTCAE). Therefore, we created a radiation dermatitis grading support system (RDGS) using a deep convolutional neural network (DCNN) and then evaluated the effectiveness of the RDGS.