AIMC Topic: Papillomaviridae

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Human papilloma virus detection in oropharyngeal carcinomas with in situ hybridisation using hand crafted morphological features and deep central attention residual networks.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society Jan 22, 2021
Human Papilloma Virus (HPV) is a major risk factor for the development of oropharyngeal cancer. Automatic detection of HPV in digitized pathology tissues using in situ hybridisation (ISH) is a difficult task due to the variability and complexity of s...
Carcinoma Attention Papillomaviridae Oropharyngeal Neoplasms Alphapapillomavirus Humans Deep Learning
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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...
Papillomavirus Infections Squamous Cell Carcinoma of Head and Neck Head and Neck Neoplasms Regression Analysis Area Under Curve Male Papillomaviridae Humans Retrospective Studies Middle Aged Oropharyngeal Neoplasms Machine Learning Female Multiparametric Magnetic Resonance Imaging ROC Curve Aged Computational Biology Aged, 80 and over Adult
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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...
Uterine Cervical Neoplasms Middle Aged Severity of Illness Index Deep Learning Image Processing, Computer-Assisted Humans Female Adult Uterine Cervical Dysplasia Papillomaviridae Colposcopy Neoplasm Invasiveness Vaginal Smears Predictive Value of Tests Papillomavirus Infections Triage Cervix Uteri Biopsy Early Detection of Cancer Datasets as Topic
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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-...
Biopsy Image Interpretation, Computer-Assisted Datasets as Topic Uterine Cervical Dysplasia Papillomaviridae Cervix Uteri Early Detection of Cancer Models, Statistical Neoplasm Grading Colposcopy Squamous Intraepithelial Lesions Humans Retrospective Studies Female Adult Uterine Cervical Neoplasms Middle Aged Deep Learning Vaginal Smears Papillomavirus Infections
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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...
Head and Neck Neoplasms Privacy Data Accuracy Image Interpretation, Computer-Assisted Papillomaviridae Survival Rate Deep Learning ROC Curve Papillomavirus Infections Humans Prognosis Retrospective Studies Tomography, X-Ray Computed
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Point-of-care cervical cancer screening using deep learning-based microholography.

Theranostics Nov 26, 2019
Most deaths (80%) from cervical cancer occur in regions lacking adequate screening infrastructures or ready access to them. In contrast, most developed countries now embrace human papillomavirus (HPV) analyses as standalone screening; this transition...
Deep Learning Cervix Uteri Early Detection of Cancer Papillomaviridae Human papillomavirus 16 Human papillomavirus 18 Humans Female Uterine Cervical Neoplasms Point-of-Care Systems
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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...
Humans Machine Learning Female Papillomavirus Infections Early Detection of Cancer Asian People Genotyping Techniques Uterine Cervical Dysplasia Papillomaviridae Sensitivity and Specificity Aged Uterine Cervical Neoplasms Aged, 80 and over Middle Aged Young Adult Adolescent Adult Genotype
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A machine learning approach for viral genome classification.

BMC bioinformatics Apr 11, 2017
BACKGROUND: Advances in cloning and sequencing technology are yielding a massive number of viral genomes. The classification and annotation of these genomes constitute important assets in the discovery of genomic variability, taxonomic characteristic...
Machine Learning Computer Simulation Papillomaviridae Hepatitis B virus Genomics Sequence Analysis, DNA Sequence Analysis, RNA HIV-1 Genome, Viral Humans Classification
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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...
Genomic Instability Papillomavirus Infections Oncogene Proteins, Viral Cell Line Humans Papillomaviridae Carcinogenesis Animals Cyclophosphamide Cattle Bovine papillomavirus 1 Recombinant Proteins
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Development of a cervical cancer progress prediction tool for human papillomavirus-positive Koreans: A support vector machine-based approach.

The Journal of international medical research May 22, 2015
OBJECTIVES: To develop a Web-based tool to draw attention to patients positive for human papillomavirus (HPV) who have a high risk of progression to cervical cancer, in order to increase compliance with follow-up examinations and facilitate good doct...
Adolescent Child Vaginal Smears Genotype Support Vector Machine Humans Sensitivity and Specificity Republic of Korea Uterine Cervical Neoplasms Female Middle Aged Age Factors Aged Disease Progression Biopsy Young Adult Asian People Adult Papillomaviridae
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