AIMC Topic: Uterine Cervical Neoplasms

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Identifying Predictors of Cervical Cancer Screening Uptake in Sub-Saharan Africa Using Machine Learning: Cross-Sectional Study.

JMIR public health and surveillance
BACKGROUND: Cervical cancer has been ranked as the fourth most common cancer affecting women, contributing to approximately 660,000 new diagnoses and 350,000 fatalities worldwide. Effective early screening has been shown to reduce cervical cancer inc...

Comparative analysis of cervical cancer classification of DPAGCHE-enhanced Pap smear images using convolutional neural network models.

PloS one
Cervical cancer remains a significant cause of female mortality worldwide, primarily due to abnormal cell growth in the cervix. This study proposes an automated classification method to enhance detection accuracy and efficiency, addressing contrast a...

Performance evaluation of machine learning models in cervical cancer diagnosis: Systematic review and meta-analysis.

European journal of cancer (Oxford, England : 1990)
INTRODUCTION: Cervical cancer is one of the most frequent malignancies worldwide and one of the leading causes of death in women. Recently, artificial intelligence-based tools have been developed for the early diagnosis of malignancies, including cer...

Criteria-calibration approaches to deep learning-based cervical cancer radiation treatment auto-planning.

Radiation oncology (London, England)
BACKGROUND: Knowledge-Based Planning (KBP) pipelines, which integrate machine learning-based models to predict dose distribution, have gained popularity in clinical radiation therapy. However, for patients with specific requirements, the trained mode...

AI-assisted cervical cytology precancerous screening for high-risk population in resource-limited regions using a compact microscope.

Nature communications
Insufficient coverage of cervical cytology screening in resource-limited areas remains a major bottleneck for women's health, as traditional centralized methods require significant investment and many qualified pathologists. Using consumer-grade elec...

Prediction of cervical cancer lymph node metastasis based on multisequence magnetic resonance imaging radiomics and deep learning features: a dual-center study.

Scientific reports
Cervical cancer is a leading cause of death from malignant tumors in women, and accurate evaluation of occult lymph node metastasis (OLNM) is crucial for optimal treatment. This study aimed to develop several predictive models-including Clinical mode...

Comparison of performance of cervical cancer grading based on acetowhite areas.

Scientific reports
Cervical cancer ranks fourth globally in terms of both incidence and mortality among women, making timely diagnosis essential for effective treatment. Although the acetowhite regions and their margins are important for cervical cancer staging, their ...

Preoperative MRI-based radiomics analysis of intra- and peritumoral regions for predicting CD3 expression in early cervical cancer.

Scientific reports
The study investigates the correlation between CD3 T-cell expression levels and cervical cancer (CC) while developing a magnetic resonance (MR) imaging-based radiomics model for preoperative prediction of CD3 T-cell expression levels. Prognostic corr...

Accuracy and acceptability of self-sampling HPV testing in cervical cancer screening: a population-based study in rural Yunnan, China.

Scientific reports
To evaluate the accuracy and acceptability of self-sampling samples for HPV testing for cervical cancer screening in rural Yunnan of China. In 2022, 3000 women aged 17-69 were recruited and provided self-sampling vaginal samples alongside provider-sa...