AIMC Topic: Vaginal Smears
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Exploring potential methylation markers for ovarian cancer from cervical scraping samples.
Human genomics
May 17, 2025
BACKGROUND: Ovarian cancer has the highest mortality rate among gynecological cancers, making early detection crucial, as the five-year survival rate drops from 92% with early-stage diagnosis compared to 31% with late-stage diagnosis. Current diagnos...
Deep learning enabled liquid-based cytology model for cervical precancer and cancer detection.
Nature communications
Apr 13, 2025
Deep learning (DL) enabled liquid-based cytology has potential for cervical cancer screening or triage. Here, we develop a DL model using whole cytology slides from 17,397 women and test it on 10,826 additional cases through a three-stage process. Th...
A deep ensemble learning approach for squamous cell classification in cervical cancer.
Scientific reports
Mar 1, 2025
Cervical cancer, arising from the cells of the cervix, the lower segment of the uterus connected to the vagina-poses a significant health threat. The microscopic examination of cervical cells using Pap smear techniques plays a crucial role in identif...
Comparison of deep transfer learning models for classification of cervical cancer from pap smear images.
Scientific reports
Jan 31, 2025
Cervical cancer is one of the most commonly diagnosed cancers worldwide, and it is particularly prevalent among women living in developing countries. Traditional classification algorithms often require segmentation and feature extraction techniques t...
BMT: A Cross-Validated ThinPrep Pap Cervical Cytology Dataset for Machine Learning Model Training and Validation.
Scientific data
Dec 28, 2024
In the past several years, a few cervical Pap smear datasets have been published for use in clinical training. However, most publicly available datasets consist of pre-segmented single cell images, contain on-image annotations that must be manually e...
Integration of AI-Assisted in Digital Cervical Cytology Training: A Comparative Study.
Cytopathology : official journal of the British Society for Clinical Cytology
Dec 8, 2024
OBJECTIVE: This study aimed to investigate the supporting role of artificial intelligence (AI) in digital cervical cytology training.
Performance of deep learning models in predicting the nugent score to diagnose bacterial vaginosis.
Microbiology spectrum
Nov 19, 2024
The Nugent score is a commonly used diagnostic tool for bacterial vaginosis. However, its accuracy depends on the skills of laboratory technicians. This study aimed to evaluate the performance of deep learning models in predicting the Nugent score to...
Detecting the impact of diagnostic procedures in Pap-positive women on anxiety using artificial neural networks.
PloS one
Oct 31, 2024
INTRODUCTION: Women who receive a result of an abnormal Papanicolaou (Pap) smear can fail to participate in follow up procedures, and this is often due to anxiety. This study aimed to apply artificial neural networks (ANN) in prediction of anxiety in...
Enhancing pap smear image classification: integrating transfer learning and attention mechanisms for improved detection of cervical abnormalities.
Biomedical physics & engineering express
Sep 30, 2024
Cervical cancer remains a major global health challenge, accounting for significant morbidity and mortality among women. Early detection through screening, such as Pap smear tests, is crucial for effective treatment and improved patient outcomes. How...
Enhancing cervical cancer cytology screening via artificial intelligence innovation.
Scientific reports
Aug 22, 2024
A double-check process helps prevent errors and ensures quality control. However, it may lead to decreased personal accountability, reduced effort, and declining quality checks. Introducing an artificial intelligence (AI)-based system in such scenari...
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