AIMC Topic: Uterine Cervical Dysplasia

Clear Filters Showing 1 to 10 of 29 articles

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...

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...

Deep learning enabled liquid-based cytology model for cervical precancer and cancer detection.

Nature communications
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...

AI-Based Identification Method for Cervical Transformation Zone Within Digital Colposcopy: Development and Multicenter Validation Study.

JMIR cancer
BACKGROUND: In low- and middle-income countries, cervical cancer remains a leading cause of death and morbidity for women. Early detection and treatment of precancerous lesions are critical in cervical cancer prevention, and colposcopy is a primary d...

Identifying Data-Driven Clinical Subgroups for Cervical Cancer Prevention With Machine Learning: Population-Based, External, and Diagnostic Validation Study.

JMIR public health and surveillance
BACKGROUND: Cervical cancer remains a major global health issue. Personalized, data-driven cervical cancer prevention (CCP) strategies tailored to phenotypic profiles may improve prevention and reduce disease burden.

A multimodal deep learning model for cervical pre-cancers and cancers prediction: Development and internal validation study.

Computers in biology and medicine
BACKGROUND: The current cervical cancer screening and diagnosis have limitations due to their subjectivity and lack of reproducibility. We describe the development of a deep learning (DL)-based diagnostic risk prediction model and evaluate its potent...

A lightweight deep learning method to identify different types of cervical cancer.

Scientific reports
Cervical cancer is the second most common cancer in women's bodies after breast cancer. Cervical cancer develops from dysplasia or cervical intraepithelial neoplasm (CIN), the early stage of the disease, and is characterized by the aberrant growth of...

Clinical evaluation of an artificial intelligence-assisted cytological system among screening strategies for a cervical cancer high-risk population.

BMC cancer
BACKGROUND: Primary cervical cancer screening and treating precancerous lesions are effective ways to prevent cervical cancer. However, the coverage rates of human papillomavirus (HPV) vaccines and routine screening are low in most developing countri...

Assessment of Efficacy and Accuracy of Cervical Cytology Screening With Artificial Intelligence Assistive System.

Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc
The role of artificial intelligence (AI) in pathology offers many exciting new possibilities for improving patient care. This study contributes to this development by identifying the viability of the AICyte assistive system for cervical screening, an...