AIMC Topic: Squamous Cell Carcinoma of Head and Neck

Clear Filters Showing 41 to 50 of 121 articles

Applying Machine Learning for Enhanced MicroRNA Analysis: A Companion Risk Tool for Oral Squamous Cell Carcinoma in Standard Care Incisional Biopsy.

Biomolecules Apr 9, 2024
Machine learning analyses within the realm of oral cancer outcomes are relatively underexplored compared to other cancer types. This study aimed to assess the performance of machine learning algorithms in identifying oral cancer patients, utilizing m...
Humans Machine Learning Algorithms Female Squamous Cell Carcinoma of Head and Neck MicroRNAs Biopsy Mouth Neoplasms Carcinoma, Squamous Cell Male Gene Expression Regulation, Neoplastic
View on PubMed DOI

Identifying potential ligand-receptor interactions based on gradient boosted neural network and interpretable boosting machine for intercellular communication analysis.

Computers in biology and medicine Feb 6, 2024
Cell-cell communication is essential to many key biological processes. Intercellular communication is generally mediated by ligand-receptor interactions (LRIs). Thus, building a comprehensive and high-quality LRI resource can significantly improve in...
Squamous Cell Carcinoma of Head and Neck Head and Neck Neoplasms Ligands Neural Networks, Computer Molecular Docking Simulation Humans
View on PubMed DOI

Machine learning based on magnetic resonance imaging and clinical parameters helps predict mesenchymal-epithelial transition factor expression in oral tongue squamous cell carcinoma: a pilot study.

Oral surgery, oral medicine, oral pathology and oral radiology Dec 27, 2023
OBJECTIVES: This study aimed to develop machine learning models to predict phosphorylated mesenchymal-epithelial transition factor (p-MET) expression in oral tongue squamous cell carcinoma (OTSCC) using magnetic resonance imaging (MRI)-derived textur...
Squamous Cell Carcinoma of Head and Neck Carcinoma, Squamous Cell Head and Neck Neoplasms Humans Reproducibility of Results Magnetic Resonance Imaging Bayes Theorem Machine Learning Pilot Projects Tongue Neoplasms Retrospective Studies
View on PubMed DOI

A deep learning and radiomics fusion model based on contrast-enhanced computer tomography improves preoperative identification of cervical lymph node metastasis of oral squamous cell carcinoma.

Clinical oral investigations Dec 27, 2023
OBJECTIVES: In this study, we constructed and validated models based on deep learning and radiomics to facilitate preoperative diagnosis of cervical lymph node metastasis (LNM) using contrast-enhanced computed tomography (CECT).
Humans Computers Squamous Cell Carcinoma of Head and Neck Head and Neck Neoplasms Lymphatic Metastasis Mouth Neoplasms Radiomics Deep Learning Lymph Nodes Retrospective Studies Tomography, X-Ray Computed Carcinoma, Squamous Cell
View on PubMed DOI

Machine Learning-Based MRI Radiogenomics for Evaluation of Response to Induction Chemotherapy in Head and Neck Squamous Cell Carcinoma.

Academic radiology Nov 18, 2023
RATIONALE AND OBJECTIVES: To develop and validate a radiogenomics model integrating clinical data, radiomics-based machine learning (RBML) classifiers, and transcriptomics data for predicting the response to induction chemotherapy (IC) in patients wi...
Male Middle Aged Treatment Outcome Squamous Cell Carcinoma of Head and Neck Female Aged Adult Induction Chemotherapy Imaging Genomics Head and Neck Neoplasms Contrast Media Magnetic Resonance Imaging Humans Machine Learning
View on PubMed DOI

Multiparametric MRI-based radiomics model for predicting human papillomavirus status in oropharyngeal squamous cell carcinoma: optimization using oversampling and machine learning techniques.

European radiology Oct 18, 2023
OBJECTIVES: To develop and validate a multiparametric MRI-based radiomics model with optimal oversampling and machine learning techniques for predicting human papillomavirus (HPV) status in oropharyngeal squamous cell carcinoma (OPSCC).
Squamous Cell Carcinoma of Head and Neck Papillomaviridae Oropharyngeal Neoplasms Multiparametric Magnetic Resonance Imaging Human Papillomavirus Viruses Male Middle Aged Papillomavirus Infections Female Aged Radiomics Machine Learning Humans Retrospective Studies
View on PubMed DOI

Prognostic significance of cyclin D1 expression pattern in HPV-negative oral and oropharyngeal carcinoma: A deep-learning approach.

Journal of oral pathology & medicine : official publication of the International Association of Oral Pathologists and the American Academy of Oral Pathology Sep 13, 2023
BACKGROUND: We aimed to establish image recognition and survival prediction models using a novel scoring system of cyclin D1 expression pattern in patients with human papillomavirus-negative oral or oropharyngeal squamous cell carcinoma.
Head and Neck Neoplasms Mouth Neoplasms Carcinoma, Squamous Cell Humans Papillomavirus Infections Cyclin D1 Deep Learning Prognosis Oropharyngeal Neoplasms Squamous Cell Carcinoma of Head and Neck Retrospective Studies
View on PubMed DOI

A Novel Deep Learning Algorithm for Human Papillomavirus Infection Prediction in Head and Neck Cancers Using Routine Histology Images.

Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc Aug 29, 2023
The etiology of head and neck squamous cell carcinoma (HNSCC) involves multiple carcinogens, such as alcohol, tobacco, and infection with human papillomavirus (HPV). Because HPV infection influences the prognosis, treatment, and survival of patients ...
Hematoxylin Head and Neck Neoplasms Papillomaviridae Eosine Yellowish-(YS) Tumor Microenvironment Deep Learning Papillomavirus Infections Squamous Cell Carcinoma of Head and Neck Humans Carcinoma, Squamous Cell
View on PubMed DOI

Development and Validation of an Automated Image-Based Deep Learning Platform for Sarcopenia Assessment in Head and Neck Cancer.

JAMA network open Aug 1, 2023
IMPORTANCE: Sarcopenia is an established prognostic factor in patients with head and neck squamous cell carcinoma (HNSCC); the quantification of sarcopenia assessed by imaging is typically achieved through the skeletal muscle index (SMI), which can b...
Female Male Middle Aged Head and Neck Neoplasms Sarcopenia Deep Learning Squamous Cell Carcinoma of Head and Neck Humans Retrospective Studies
View on PubMed DOI

A CT-based Deep Learning Radiomics Nomogram for the Prediction of EGFR Mutation Status in Head and Neck Squamous Cell Carcinoma.

Academic radiology Jul 21, 2023
RATIONALE AND OBJECTIVES: Accurately assessing epidermal growth factor receptor (EGFR) mutation status in head and neck squamous cell carcinoma (HNSCC) patients is crucial for prognosis and treatment selection. This study aimed to construct and valid...
Nomograms Squamous Cell Carcinoma of Head and Neck Head and Neck Neoplasms Mutation Humans ErbB Receptors Tomography, X-Ray Computed Retrospective Studies Radiomics Deep Learning
View on PubMed DOI
Popular Topics
Recent Journals