Comparison of Machine-Learning and Deep-Learning Methods for the Prediction of Osteoradionecrosis Resulting From Head and Neck Cancer Radiation Therapy
Purpose: Deep-learning (DL) techniques have been successful in disease-prediction tasks and could improve the prediction of mandible osteoradionecrosis (ORN) resulting from head and neck cancer (HNC) radiation therapy. In this study, we retrospectively compared the performance of DL algorithms and t...
Main Authors: | Brandon Reber, BS, Lisanne Van Dijk, PhD, Brian Anderson, PhD, Abdallah Sherif Radwan Mohamed, MD, PhD, Clifton Fuller, MD, PhD, Stephen Lai, MD, PhD, Kristy Brock, PhD |
---|---|
Format: | Article |
Language: | English |
Published: |
Elsevier
2023-07-01
|
Series: | Advances in Radiation Oncology |
Online Access: | http://www.sciencedirect.com/science/article/pii/S245210942200269X |
Similar Items
-
NTCP Modeling of Late Effects for Head and Neck Cancer: A Systematic Review
by: Sonja Stieb, MD, et al.
Published: (2021-06-01) -
A Custom Mouthpiece With Lip Bumper for Osteoradionecrosis Risk Reduction After Carbon-Ion Radiation Therapy for Adenoid Cystic Carcinoma of the Lip
by: Hiroaki Ikawa, DDS, PhD, et al.
Published: (2023-01-01) -
Gemini Anastomosis for Dual Venous Anastomosis in Head and Neck Reconstruction
by: Atsumori Hamahata, MD, PhD, et al.
Published: (2023-01-01) -
Machine Learning-Based Quality Assurance for Automatic Segmentation of Head-and-Neck Organs-at-Risk in Radiotherapy
by: Shunyao Luan PhD, et al.
Published: (2023-02-01) -
The Kiss Flap Technique in Head and Neck Surgery - an Alternative Concept for Reconstruction of Extensive Defects
by: Jakub Opyrchal, MD, et al.
Published: (2024-01-01)