AIMC Topic: Colposcopy
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Scrutinizing high-risk patients from ASC-US cytology via a deep learning model.
Cancer cytopathology
Mar 15, 2022
BACKGROUND: Atypical squamous cells of undetermined significance (ASC-US) is the most frequent but ambiguous abnormal Papanicolaou (Pap) interpretation and is generally triaged by high-risk human papillomavirus (hrHPV) testing before colposcopy. This...
Deep learning based cervical screening by the cross-modal integration of colposcopy, cytology, and HPV test.
International journal of medical informatics
Dec 28, 2021
PURPOSE: To develop and evaluate the colposcopy based deep learning model using all kinds of cervical images for cervical screening, and investigate the synergetic benefits of the colposcopy, the cytology test, and the HPV test for improving cervical...
Diagnosis of Cervical Cancer based on Ensemble Deep Learning Network using Colposcopy Images.
BioMed research international
May 4, 2021
Traditional screening of cervical cancer type classification majorly depends on the pathologist's experience, which also has less accuracy. Colposcopy is a critical component of cervical cancer prevention. In conjunction with precancer screening and ...
Development and validation of an artificial intelligence system for grading colposcopic impressions and guiding biopsies.
BMC medicine
Dec 22, 2020
BACKGROUND: Colposcopy diagnosis and directed biopsy are the key components in cervical cancer screening programs. However, their performance is limited by the requirement for experienced colposcopists. This study aimed to develop and validate a Colp...
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 Dysplasia
Papillomaviridae
Colposcopy
Predictive Value of Tests
Triage
Biopsy
Datasets as Topic
Uterine Cervical Neoplasms
Middle Aged
Severity of Illness Index
Deep Learning
Image Processing, Computer-Assisted
Humans
Vaginal Smears
Female
Papillomavirus Infections
Adult
Cervix Uteri
Early Detection of Cancer
Neoplasm Invasiveness
Classification of cervical neoplasms on colposcopic photography using deep learning.
Scientific reports
Aug 12, 2020
Colposcopy is widely used to detect cervical cancers, but experienced physicians who are needed for an accurate diagnosis are lacking in developing countries. Artificial intelligence (AI) has been recently used in computer-aided diagnosis showing rem...
The artificial intelligence-assisted cytology diagnostic system in large-scale cervical cancer screening: A population-based cohort study of 0.7 million women.
Cancer medicine
Jul 22, 2020
BACKGROUND: Adequate cytology is limited by insufficient cytologists in a large-scale cervical cancer screening. We aimed to develop an artificial intelligence (AI)-assisted cytology system in cervical cancer screening program.
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-...
Uterine Cervical Neoplasms
Middle Aged
Deep Learning
Vaginal Smears
Papillomavirus Infections
Cervix Uteri
Early Detection of Cancer
Models, Statistical
Neoplasm Grading
Biopsy
Humans
Retrospective Studies
Female
Adult
Colposcopy
Squamous Intraepithelial Lesions
Image Interpretation, Computer-Assisted
Datasets as Topic
Uterine Cervical Dysplasia
Papillomaviridae
The challenges of colposcopy for cervical cancer screening in LMICs and solutions by artificial intelligence.
BMC medicine
Jun 3, 2020
BACKGROUND: The World Health Organization (WHO) called for global action towards the elimination of cervical cancer. One of the main strategies is to screen 70% of women at the age between 35 and 45 years and 90% of women managed appropriately by 203...
Automatic CIN Grades Prediction of Sequential Cervigram Image Using LSTM With Multistate CNN Features.
IEEE journal of biomedical and health informatics
Jun 13, 2019
Cervical cancer ranks as the second most common cancer in women worldwide. In clinical practice, colposcopy is an indispensable part of screening for cervical intraepithelial neoplasia (CIN) grades and cervical cancer but exhibits high misdiagnosis r...
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