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Head and Neck Neoplasms

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Convolutional neural network based anatomical site identification for laryngoscopy quality control: A multicenter study.

American journal of otolaryngology Nov 24, 2022
OBJECTIVES: Video laryngoscopy is an important diagnostic tool for head and neck cancers. The artificial intelligence (AI) system has been shown to monitor blind spots during esophagogastroduodenoscopy. This study aimed to test the performance of AI-...
Head and Neck Neoplasms Laryngoscopy Artificial Intelligence Retrospective Studies Humans Neural Networks, Computer
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Comparison of atlas-based and deep learning methods for organs at risk delineation on head-and-neck CT images using an automated treatment planning system.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology Nov 1, 2022
BACKGROUND AND PURPOSE: To investigate the performance of head-and-neck (HN) organs-at-risk (OAR) automatic segmentation (AS) using four atlas-based (ABAS) and two deep learning (DL) solutions.
Humans Head and Neck Neoplasms Organs at Risk Radiotherapy Planning, Computer-Assisted Tomography, X-Ray Computed Deep Learning
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Clinical target volume segmentation based on gross tumor volume using deep learning for head and neck cancer treatment.

Medical dosimetry : official journal of the American Association of Medical Dosimetrists Oct 21, 2022
Accurate clinical target volume (CTV) delineation is important for head and neck intensity-modulated radiation therapy. However, delineation is time-consuming and susceptible to interobserver variability (IOV). Based on a manual contouring process co...
Humans Head and Neck Neoplasms Radiotherapy Planning, Computer-Assisted Tumor Burden Tomography, X-Ray Computed Deep Learning
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Efficient dose-volume histogram-based pretreatment patient-specific quality assurance methodology with combined deep learning and machine learning models for volumetric modulated arc radiotherapy.

Medical physics Oct 17, 2022
BACKGROUND: Weak correlation between gamma passing rates and dose differences in target volumes and organs at risk (OARs) has been reported in several studies. Evaluation on the differences between planned dose-volume histogram (DVH) and reconstructe...
Radiotherapy Planning, Computer-Assisted Radiotherapy Dosage Radiotherapy, Intensity-Modulated Deep Learning Head and Neck Neoplasms Organs at Risk Humans Machine Learning
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DeepClassPathway: Molecular pathway aware classification using explainable deep learning.

European journal of cancer (Oxford, England : 1990) Sep 30, 2022
OBJECTIVE: HPV-associated head and neck cancer is correlated with favorable prognosis; however, its underlying biology is not fully understood. We propose an explainable convolutional neural network (CNN) classifier, DeepClassPathway, that predicts H...
Neural Networks, Computer Male Papillomavirus Infections Squamous Cell Carcinoma of Head and Neck Head and Neck Neoplasms Deep Learning Humans
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Clinical evaluation of deep learning and atlas-based auto-segmentation for critical organs at risk in radiation therapy.

Journal of medical radiation sciences Sep 23, 2022
INTRODUCTION: Contouring organs at risk (OARs) is a time-intensive task that is a critical part of radiation therapy. Atlas-based automatic segmentation has shown some success at reducing this time burden on practitioners; however, this method often ...
Head and Neck Neoplasms Tomography, X-Ray Computed Humans Organs at Risk Radiotherapy Planning, Computer-Assisted Deep Learning Image Processing, Computer-Assisted
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Identifying Drug Targets of Oral Squamous Cell Carcinoma through a Systems Biology Method and Genome-Wide Microarray Data for Drug Discovery by Deep Learning and Drug Design Specifications.

International journal of molecular sciences Sep 8, 2022
In this study, we provide a systems biology method to investigate the carcinogenic mechanism of oral squamous cell carcinoma (OSCC) in order to identify some important biomarkers as drug targets. Further, a systematic drug discovery method with a dee...
Metformin Gefitinib NF-kappa B Mouth Neoplasms Humans Biomarkers Drug Design Deep Learning Drug Discovery Gene Expression Regulation, Neoplastic Systems Biology Squamous Cell Carcinoma of Head and Neck Head and Neck Neoplasms Carcinoma, Squamous Cell Biomarkers, Tumor
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A deep learning-based model predicts survival for patients with laryngeal squamous cell carcinoma: a large population-based study.

European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery Aug 28, 2022
OBJECTIVES: To assess the performance of DeepSurv, a deep learning-based model in the survival prediction of laryngeal squamous cell carcinoma (LSCC) using the Surveillance, Epidemiology, and End Results (SEER) database.
Laryngeal Neoplasms Head and Neck Neoplasms Neoplasm Staging Carcinoma, Squamous Cell Humans Deep Learning Prognosis Squamous Cell Carcinoma of Head and Neck
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Clinical Validation of a Deep-Learning Segmentation Software in Head and Neck: An Early Analysis in a Developing Radiation Oncology Center.

International journal of environmental research and public health Jul 25, 2022
BACKGROUND: Organs at risk (OARs) delineation is a crucial step of radiotherapy (RT) treatment planning workflow. Time-consuming and inter-observer variability are main issues in manual OAR delineation, mainly in the head and neck (H & N) district. D...
Head and Neck Neoplasms Deep Learning Radiation Oncology Image Processing, Computer-Assisted Humans Radiotherapy Planning, Computer-Assisted Software
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Comparative evaluation of a prototype deep learning algorithm for autosegmentation of normal tissues in head and neck radiotherapy.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology Jul 9, 2022
PURPOSE: To introduce and validate a newly developed deep-learning (DL) auto-segmentation algorithm for head and neck (HN) organs at risk (OARs) and to compare its performance with a published commercial algorithm.
Head and Neck Neoplasms Organs at Risk Radiotherapy Planning, Computer-Assisted Reproducibility of Results Deep Learning Humans Algorithms
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