The prognostic value of pathologic lymph node imaging using deep learning-based outcome prediction in oropharyngeal cancer patients
Open Access
- 14 February 2025
- journal article
- Published by Elsevier in Physics and Imaging in Radiation Oncology
- Vol. 33, 100733
Abstract
No abstract availableKeywords
Funding Information
- China Scholarship Council
- Hanarth Fund Foundation
This publication has 24 references indexed in Scilit:
- Reviewing the epidemiology of head and neck cancer: definitions, trends and risk factorsBritish Dental Journal, 2022
- Head and neck cancer predictive risk estimator to determine control and therapeutic outcomes of radiotherapy (HNC-PREDICTOR): development, international multi-institutional validation, and web implementation of clinic-ready model-based risk stratification for head and neck cancerEuropean Journal of Cancer, 2022
- Deep learning based time-to-event analysis with PET, CT and joint PET/CT for head and neck cancer prognosisComputer Methods and Programs in Biomedicine, 2022
- Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 CountriesCA: A Cancer Journal for Clinicians, 2021
- First experience with model-based selection of head and neck cancer patients for proton therapyRadiotherapy and Oncology, 2020
- Combined CT radiomics of primary tumor and metastatic lymph nodes improves prediction of loco-regional control in head and neck cancerScientific Reports, 2019
- The prognostic value of CT-based image-biomarkers for head and neck cancer patients treated with definitive (chemo-)radiationOral Oncology, 2019
- Human Papillomavirus and Survival of Patients with Oropharyngeal CancerNew England Journal of Medicine, 2010
- Prognostic factors in oropharyngeal cancer – analysis of 627 cases receiving definitive radiotherapyActa Oncologica, 2009
- Statistical Aspects of the Analysis of Data From Retrospective Studies of DiseaseJNCI: Journal of the National Cancer Institute, 1959