AIMC Topic: Papillomavirus Infections

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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 Support Vector Machine Humans DNA, Viral Machine Learning Stomach Neoplasms Tumor Microenvironment High-Throughput Nucleotide Sequencing Biomarkers, Tumor Genome, Viral Epstein-Barr Virus Infections Neoplasms Tumor Virus Infections Herpesvirus 4, Human Kaplan-Meier Estimate Transcriptome Mutation Papillomaviridae RNA-Seq Leukocytes Oncogenic Viruses Genetic Variation
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Cystic cervical lymph nodes of papillary thyroid carcinoma, tuberculosis and human papillomavirus positive oropharyngeal squamous cell carcinoma: utility of deep learning in their differentiation on CT.

American journal of otolaryngology Apr 9, 2021
OBJECTIVES: Cervical lymph nodes with internal cystic changes are seen with several pathologies, including papillary thyroid carcinoma (PTC), tuberculosis (TB), and HPV-positive oropharyngeal squamous cell carcinoma (HPV+OPSCC). Differentiating these...
Lymph Nodes Squamous Cell Carcinoma of Head and Neck Neck Diagnosis, Differential Tuberculosis Humans Papillomaviridae Tomography, X-Ray Computed Thyroid Cancer, Papillary Female Oropharyngeal Neoplasms Male Deep Learning Thyroid Neoplasms Papillomavirus Infections
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Use of Deep Learning to Analyze Social Media Discussions About the Human Papillomavirus Vaccine.

JAMA network open Nov 2, 2020
IMPORTANCE: Human papillomavirus (HPV) vaccine hesitancy or refusal is common among parents of adolescents. An understanding of public perceptions from the perspective of behavior change theories can facilitate effective and targeted vaccine promotio...
Retrospective Studies Deep Learning Surveys and Questionnaires Cohort Studies Papillomavirus Vaccines Papillomavirus Infections Humans Health Knowledge, Attitudes, Practice Social Media Patient Acceptance of Health Care Social Networking
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Oropharyngeal squamous cell carcinoma: radiomic machine-learning classifiers from multiparametric MR images for determination of HPV infection status.

Scientific reports Oct 16, 2020
We investigated the ability of machine-learning classifiers on radiomics from pre-treatment multiparametric magnetic resonance imaging (MRI) to accurately predict human papillomavirus (HPV) status in patients with oropharyngeal squamous cell carcinom...
ROC Curve Computational Biology Papillomavirus Infections Squamous Cell Carcinoma of Head and Neck Head and Neck Neoplasms Regression Analysis Aged Aged, 80 and over Adult Male Middle Aged Area Under Curve Papillomaviridae Oropharyngeal Neoplasms Multiparametric Magnetic Resonance Imaging Humans Machine Learning Retrospective Studies Female
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Artificial intelligence-assisted cytology for detection of cervical intraepithelial neoplasia or invasive cancer: A multicenter, clinical-based, observational study.

Gynecologic oncology Aug 16, 2020
OBJECTIVE: Artificial intelligence (AI) could automatedly detect abnormalities in digital cytological images, however, the effect in cervical cancer screening is inconclusive. We aim to evaluate the performance of AI-assisted cytology for the detecti...
Predictive Value of Tests Triage Biopsy Datasets as Topic Vaginal Smears Humans Uterine Cervical Dysplasia Papillomaviridae Papillomavirus Infections Colposcopy Female Cervix Uteri Uterine Cervical Neoplasms Adult Early Detection of Cancer Middle Aged Neoplasm Invasiveness Severity of Illness Index Deep Learning Image Processing, Computer-Assisted
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The application of deep learning based diagnostic system to cervical squamous intraepithelial lesions recognition in colposcopy images.

Scientific reports Jul 15, 2020
Background Deep learning has presented considerable potential and is gaining more importance in computer assisted diagnosis. As the gold standard for pathologically diagnosing cervical intraepithelial lesions and invasive cervical cancer, colposcopy-...
Humans Neoplasm Grading Deep Learning Retrospective Studies Biopsy Vaginal Smears Papillomaviridae Female Image Interpretation, Computer-Assisted Papillomavirus Infections Colposcopy Adult Datasets as Topic Cervix Uteri Squamous Intraepithelial Lesions Uterine Cervical Dysplasia Uterine Cervical Neoplasms Early Detection of Cancer Middle Aged Models, Statistical
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Machine Learning Based Radiomic HPV Phenotyping of Oropharyngeal SCC: A Feasibility Study Using MRI.

The Laryngoscope Jul 13, 2020
OBJECTIVES: To investigate whether a radiomic MRI feature-based prediction model can differentiate oropharyngeal squamous cell carcinoma (SCC) according to the human papillomavirus (HPV) status.
Middle Aged ROC Curve Papillomavirus Infections Logistic Models Squamous Cell Carcinoma of Head and Neck Magnetic Resonance Imaging Predictive Value of Tests Feasibility Studies Oropharyngeal Neoplasms Alphapapillomavirus Machine Learning Retrospective Studies Female Humans Aged Male
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Machine Learning Prediction of Extracapsular Extension in Human Papillomavirus-Associated Oropharyngeal Squamous Cell Carcinoma.

Otolaryngology--head and neck surgery : official journal of American Academy of Otolaryngology-Head and Neck Surgery Jun 30, 2020
OBJECTIVE: To determine whether machine learning (ML) can predict the presence of extracapsular extension (ECE) prior to treatment, using common oncologic variables, in patients with human papillomavirus (HPV)-associated oropharyngeal squamous cell c...
Oropharyngeal Neoplasms Alphapapillomavirus Extranodal Extension Middle Aged ROC Curve Papillomavirus Infections Logistic Models Squamous Cell Carcinoma of Head and Neck Databases, Factual Prognosis Humans Retrospective Studies Machine Learning Female Aged Male
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Machine learning-based CT texture analysis to predict HPV status in oropharyngeal squamous cell carcinoma: comparison of 2D and 3D segmentation.

European radiology Jun 26, 2020
OBJECTIVE: To compare the CT texture feature reproducibility of 2D and 3D segmentations and their machine learning (ML)-based classifications for predicting human papilloma virus (HPV) status in oropharyngeal squamous cell carcinoma (OPSCC).
Diagnosis, Differential Area Under Curve Observer Variation Humans Alphapapillomavirus Machine Learning Imaging, Three-Dimensional Algorithms Image Processing, Computer-Assisted Retrospective Studies Papillomavirus Infections Tomography, X-Ray Computed Squamous Cell Carcinoma of Head and Neck Female Head and Neck Neoplasms Reproducibility of Results Regression Analysis Male
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Privacy-preserving distributed learning of radiomics to predict overall survival and HPV status in head and neck cancer.

Scientific reports Mar 11, 2020
A major challenge in radiomics is assembling data from multiple centers. Sharing data between hospitals is restricted by legal and ethical regulations. Distributed learning is a technique, enabling training models on multicenter data without data lea...
Data Accuracy Humans Deep Learning Image Interpretation, Computer-Assisted Prognosis ROC Curve Papillomaviridae Retrospective Studies Papillomavirus Infections Tomography, X-Ray Computed Head and Neck Neoplasms Survival Rate Privacy
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