AIMC Topic: Squamous Cell Carcinoma of Head and Neck

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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.
Deep Learning Squamous Cell Carcinoma of Head and Neck Head and Neck Neoplasms Neoplasm Staging Laryngeal Neoplasms Humans Prognosis Carcinoma, Squamous Cell
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Intelligent Deep Learning Enabled Oral Squamous Cell Carcinoma Detection and Classification Using Biomedical Images.

Computational intelligence and neuroscience Jun 30, 2022
Oral cancer is one of the lethal diseases among the available malignant tumors globally, and it has become a challenging health issue in developing and low-to-middle income countries. The prognosis of oral cancer remains poor because over 50% of pati...
Head and Neck Neoplasms Mouth Neoplasms Humans Carcinoma, Squamous Cell Deep Learning Squamous Cell Carcinoma of Head and Neck
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A machine learning model for separating epithelial and stromal regions in oral cavity squamous cell carcinomas using H&E-stained histology images: A multi-center, retrospective study.

Oral oncology Jun 8, 2022
OBJECTIVE: Tissue slides from Oral cavity squamous cell carcinoma (OC-SCC), particularly the epithelial regions, hold morphologic features that are both diagnostic and prognostic. Yet, previously developed approaches for automated epithelium segmenta...
Deep Learning Image Processing, Computer-Assisted Squamous Cell Carcinoma of Head and Neck Head and Neck Neoplasms Humans Machine Learning Retrospective Studies Carcinoma, Squamous Cell Mouth Neoplasms
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Histopathology-Based Diagnosis of Oral Squamous Cell Carcinoma Using Deep Learning.

Journal of dental research Apr 21, 2022
Oral squamous cell carcinoma (OSCC) is prevalent around the world and is associated with poor prognosis. OSCC is typically diagnosed from tissue biopsy sections by pathologists who rely on their empirical experience. Deep learning models may improve ...
Humans Carcinoma, Squamous Cell Deep Learning Squamous Cell Carcinoma of Head and Neck Head and Neck Neoplasms Mouth Neoplasms
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The viral expression and immune status in human cancers and insights into novel biomarkers of immunotherapy.

BMC cancer Nov 5, 2021
BACKGROUND: Viral infections are prevalent in human cancers and they have great diagnostic and theranostic values in clinical practice. Recently, their potential of shaping the tumor immune microenvironment (TIME) has been related to the immunotherap...
Immunotherapy Papillomavirus Infections Squamous Cell Carcinoma of Head and Neck Head and Neck Neoplasms Biomarkers, Tumor Neoplasms Transcriptome RNA-Seq Mutation Leukocytes Genetic Variation High-Throughput Nucleotide Sequencing Genome, Viral Support Vector Machine DNA, Viral Epstein-Barr Virus Infections Herpesvirus 4, Human Humans Machine Learning Stomach Neoplasms Tumor Microenvironment Tumor Virus Infections Kaplan-Meier Estimate Papillomaviridae Oncogenic Viruses
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Estimating the conditional probability of developing human papilloma virus related oropharyngeal cancer by combining machine learning and inverse Bayesian modelling.

PLoS computational biology Aug 20, 2021
The epidemic increase in the incidence of Human Papilloma Virus (HPV) related Oropharyngeal Squamous Cell Carcinomas (OPSCCs) in several countries worldwide represents a significant public health concern. Although gender neutral HPV vaccination progr...
Humans Machine Learning Female Aged Adult Male Middle Aged Squamous Cell Carcinoma of Head and Neck Bayes Theorem Alphapapillomavirus SEER Program Probability Oropharyngeal Neoplasms
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Prediction of the local treatment outcome in patients with oropharyngeal squamous cell carcinoma using deep learning analysis of pretreatment FDG-PET images.

BMC cancer Aug 6, 2021
BACKGROUND: This study aimed to assess the utility of deep learning analysis using pretreatment FDG-PET images to predict local treatment outcome in oropharyngeal squamous cell carcinoma (OPSCC) patients.
Disease Management Fluorodeoxyglucose F18 Kaplan-Meier Estimate Oropharyngeal Neoplasms Neoplasm Staging Female Workflow Aged Combined Modality Therapy Aged, 80 and over Image Processing, Computer-Assisted Positron-Emission Tomography Humans Adult Treatment Outcome Middle Aged Prognosis Squamous Cell Carcinoma of Head and Neck Biomarkers, Tumor Clinical Decision-Making Positron Emission Tomography Computed Tomography Deep Learning Male ROC Curve
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A prediction model for degree of differentiation for resectable locally advanced esophageal squamous cell carcinoma based on CT images using radiomics and machine-learning.

The British journal of radiology Jul 8, 2021
OBJECTIVE: To propose the prediction model for degree of differentiation for locally advanced esophageal cancer patients from the planning CT image by radiomics analysis with machine learning.
Squamous Cell Carcinoma of Head and Neck Head and Neck Neoplasms Cell Differentiation Neoplasm Staging Adult Prognosis Male Middle Aged Retrospective Studies Tomography, X-Ray Computed Models, Theoretical Humans Female Machine Learning Aged
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Oncological, Surgical and Functional Outcomes of Transoral Robotic Cordectomy for Early Glottic Carcinoma.

Journal of voice : official journal of the Voice Foundation Jun 3, 2021
OBJECTIVE: To investigate oncological, surgical and functional outcomes of transoral robotic surgery cordectomy (TORS-Co).
Squamous Cell Carcinoma of Head and Neck Head and Neck Neoplasms Robotics Robotic Surgical Procedures Humans Carbon Dioxide Retrospective Studies Laryngeal Neoplasms Carcinoma, Squamous Cell Postoperative Complications Treatment Outcome
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Deep Learning for Fully Automated Prediction of Overall Survival in Patients with Oropharyngeal Cancer Using FDG-PET Imaging.

Clinical cancer research : an official journal of the American Association for Cancer Research May 4, 2021
PURPOSE: Accurate prognostic stratification of patients with oropharyngeal squamous cell carcinoma (OPSCC) is crucial. We developed an objective and robust deep learning-based fully-automated tool called the DeepPET-OPSCC biomarker for predicting ove...
Squamous Cell Carcinoma of Head and Neck Positron-Emission Tomography Humans Male Head and Neck Neoplasms Fluorodeoxyglucose F18 Prognosis Middle Aged Predictive Value of Tests Oropharyngeal Neoplasms Female Deep Learning Survival Rate Cohort Studies Radiopharmaceuticals
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