AIMC Topic: Papillomavirus Infections

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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.
Humans Machine Learning Retrospective Studies Female Aged Feasibility Studies Oropharyngeal Neoplasms Alphapapillomavirus Male Middle Aged ROC Curve Papillomavirus Infections Logistic Models Squamous Cell Carcinoma of Head and Neck Magnetic Resonance Imaging Predictive Value of Tests
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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 ROC Curve Papillomavirus Infections Logistic Models Female Squamous Cell Carcinoma of Head and Neck Databases, Factual Aged Prognosis Male Retrospective Studies Middle Aged Humans Machine Learning
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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).
Papillomavirus Infections Squamous Cell Carcinoma of Head and Neck Head and Neck Neoplasms Regression Analysis Reproducibility of Results Male Imaging, Three-Dimensional Image Processing, Computer-Assisted Diagnosis, Differential Area Under Curve Observer Variation Alphapapillomavirus Humans Retrospective Studies Tomography, X-Ray Computed Female Machine Learning Algorithms
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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...
Privacy Survival Rate Humans Data Accuracy Deep Learning ROC Curve Image Interpretation, Computer-Assisted Papillomavirus Infections Papillomaviridae Prognosis Head and Neck Neoplasms Retrospective Studies Tomography, X-Ray Computed
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Machine Learning Interpretation of Extended Human Papillomavirus Genotyping by Onclarity in an Asian Cervical Cancer Screening Population.

Journal of clinical microbiology Nov 22, 2019
This study aimed (i) to compare the performance of the BD Onclarity human papillomavirus (HPV) assay with the Cobas HPV test in identifying cervical intraepithelial neoplasia 2/3 or above (CIN2/3+) in an Asian screening population and (ii) to explore...
Middle Aged Adolescent Genotype Papillomavirus Infections Genotyping Techniques Uterine Cervical Dysplasia Papillomaviridae Early Detection of Cancer Humans Asian People Machine Learning Young Adult Female Aged Adult Aged, 80 and over Sensitivity and Specificity Uterine Cervical Neoplasms
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TEPAPA: a novel in silico feature learning pipeline for mining prognostic and associative factors from text-based electronic medical records.

Scientific reports Jul 31, 2017
Vast amounts of clinically relevant text-based variables lie undiscovered and unexploited in electronic medical records (EMR). To exploit this untapped resource, and thus facilitate the discovery of informative covariates from unstructured clinical n...
Head and Neck Neoplasms Natural Language Processing Supervised Machine Learning Data Mining Male Middle Aged Electronic Health Records Papillomavirus Infections Humans Female Squamous Cell Carcinoma of Head and Neck Prognosis Aged
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Leveraging machine learning-based approaches to assess human papillomavirus vaccination sentiment trends with Twitter data.

BMC medical informatics and decision making Jul 5, 2017
BACKGROUND: As one of the serious public health issues, vaccination refusal has been attracting more and more attention, especially for newly approved human papillomavirus (HPV) vaccines. Understanding public opinion towards HPV vaccines, especially ...
Vaccination Humans Social Media Health Knowledge, Attitudes, Practice Machine Learning Public Opinion Papillomavirus Vaccines Papillomavirus Infections
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Mutagenic Potential ofBos taurus Papillomavirus Type 1 E6 Recombinant Protein: First Description.

BioMed research international Dec 9, 2015
Bovine papillomavirus (BPV) is considered a useful model to study HPV oncogenic process. BPV interacts with the host chromatin, resulting in DNA damage, which is attributed to E5, E6, and E7 viral oncoproteins activity. However, the oncogenic mechani...
Bovine papillomavirus 1 Papillomavirus Infections Humans Cell Line Animals Genomic Instability Carcinogenesis Cattle Oncogene Proteins, Viral Cyclophosphamide Recombinant Proteins Papillomaviridae
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Deep Learning-Enhanced Hand-Driven Microfluidic Chip for Multiplexed Nucleic Acid Detection Based on RPA/CRISPR.

Advanced science (Weinheim, Baden-Wurttemberg, Germany) Jun 1, 2025
The early detection of high-risk human papillomavirus (HR-HPV) is crucial for the assessment and improvement of prognosis in cervical cancer. However, existing PCR-based screening methods suffer from inadequate accessibility, which dampens the enthus...
Humans Female Nucleic Acid Amplification Techniques Clustered Regularly Interspaced Short Palindromic Repeats Lab-On-A-Chip Devices Human papillomavirus 16 Human papillomavirus 18 Uterine Cervical Neoplasms Deep Learning Papillomavirus Infections Early Detection of Cancer
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[Construction and preliminary validation of machine learning predictive models for cervical cancer screening based on human DNA methylation].

Zhonghua zhong liu za zhi [Chinese journal of oncology] Feb 23, 2025
Using methylation characteristics of human genes to construct machine learning predictive models for screening cervical cancer and precancerous lesions. Human DNA methylation detection was performed on 224 cervical exfoliated cell specimens from th...
Early Detection of Cancer Bayes Theorem Humans Uterine Cervical Dysplasia Female Machine Learning Middle Aged Adult Algorithms Papillomavirus Infections Uterine Cervical Neoplasms Support Vector Machine DNA Methylation
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