Department of Biomedical Engineering, Gil Medical Center, College of Medicine, Gachon University, 21 Namdong-daero 774 Beon-gil, Namdong-gu, Incheon 21565, Korea.
Published: May 2022
AI Article Synopsis
Article Abstract
Cervical cancer is one of the main causes of death from cancer in women. However, it can be treated successfully at an early stage. This study aims to propose an image processing algorithm based on acetowhite, which is an important criterion for diagnosing cervical cancer, to increase the accuracy of the deep learning classification model. Then, we mainly compared the performance of the model, the original image without image processing, a mask image made with acetowhite as the region of interest, and an image using the proposed algorithm. In conclusion, the deep learning classification model based on images with the proposed algorithm achieved an accuracy of 81.31%, which is approximately 9% higher than the model with original images and approximately 4% higher than the model with acetowhite mask images. Our study suggests that the proposed algorithm based on acetowhite could have a better performance than other image processing algorithms for classifying stages of cervical images.
Patients admitted to Uganda Cancer Institute (UCI) have their non-medical needs provided by caregivers called "attendants" who are predominantly female family members. This provides a unique opportunity to provide free screening among attendants during their free time at the hospital. The objective of this qualitative focus group study was to understand knowledge of and facilitators and barriers to cervical cancer screening among attendants at the UCI.
To effectively prevent cervical cancer, a leading cause of global morbidity and mortality among women, widespread adoption of the HPV vaccine has a well-established link to human papillomavirus (HPV) infection. HPV vaccine must be the vaccine's effectiveness in reducing HPV infections, and subsequent cervical lesions have been extensively demonstrated, marking a pivotal milestone in public health. Important research highlights the vaccine's safety profile, allaying worries and promoting trust in its application.
Background: Cervical cancer burden in South Asia is among the highest globally. Due to the lack of national immunization programs, the prevalence of human papillomavirus (HPV) infection and vaccine uptake remains unknown. This systematic review and meta-analysis aim to determine the prevalence of HPV vaccine uptake in South Asia.
Introduction: To examine the associations of neighborhood socioeconomic status (nSES), ethnic enclaves, residential Black segregation with screening for breast, cervical and colorectal (CRC) cancers across the state of Texas (TX).
Methods: Using an ecologic study design, spatial clustering of low breast, cervical and CRC screening rates were identified across TX census tracts using local Moran's I statistics. Binomial spatial probit regression was used to estimate the associations between nSES, Hispanic/Latino and Asian American (AA) ethnic enclave neighborhoods and residential Black segregation with geospatial clusters of low screening, adjusting for behavioral characteristics.
This study aimed to comprehensively examine the association of gallstones, cholecystectomy, and cancer risk. Multivariable logistic regressions were performed to estimate the observational associations of gallstones and cholecystectomy with cancer risk, using data from a nationwide cohort involving 239 799 participants. General and gender-specific two-sample Mendelian randomization (MR) analysis was further conducted to assess the causalities of the observed associations.
