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Deep Learning-based Classification and Prediction of Radiation Dermatitis in Head and Neck Patients

Head and Neck Cancer Clinical Trial

Official title:
Deep Learning-based Classification and Prediction of Radiation Dermatitis in Head and Neck

Clinical Trial Summary

to develop a deep learning-based model to grade the severity of radiation dermatitis (RD) and predict the severity of radiation dermatitis in patients with head and neck cancer undergoing radiotherapy, so as to provide support for doctors' diagnosis and prediction.

Clinical Trial Description

1. Image acquisition The images of the neck area were collected from the enrolled patients one week before and every week during radiotherapy. The photographs were taken from three angles (front, left and right oblique) of the neck area. 2. Grading evaluation Each image was individually graded by three experienced radiotherapy experts according to the RD criteria of RTOG 3. Data analysis Construct a dermatitis grading model basing on deep learning. Evaluate the performance of model using accuracy, precision, recall, F1-measure, dice value. ;

Study Design

Related Conditions & MeSH terms

Clinical Trial Details
NCT number NCT05607225
Study type Observational
Source Cancer Institute and Hospital, Chinese Academy of Medical Sciences
Contact Li Ma, MD
Phone 86-755-66618168
Email ml_1990@126.com
Status Recruiting
Phase
Start date July 1, 2022
Completion date June 30, 2025
View Details
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