Addressing cervical cancer screening disparities through advances in artificial intelligence and nanotechnologies for cellular profiling

2021 ◽  
Vol 2 (1) ◽  
pp. 011303
Author(s):  
Zhenzhong Yang ◽  
Jack Francisco ◽  
Alexandra S. Reese ◽  
David R. Spriggs ◽  
Hyungsoon Im ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Cervical Cancer ◽  
Cancer Screening ◽  
Cervical Cancer Screening ◽  
Cancer Screening Disparities

scholarly journals Automated Quantitative Cytology Imaging Analysis System in Cervical Cancer Screening in Shanxi Province, China

2017 ◽  
Vol 6 (2) ◽  
pp. 51 ◽  
Author(s):  
Yan Dong ◽  
Jigeng Bai ◽  
Yuping Zhang ◽  
Guangjie Shang ◽  
Yan Zhao ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Cervical Cancer ◽  
Cancer Screening ◽  
Cervical Cancer Screening ◽  
Population Based ◽  
Shanxi Province ◽  
Detection Rates ◽  
Screening Programs ◽  
Quantitative Cytology ◽  
Automated Platform

Purpose: In China the number of pathologists is far from being enough to meet the demands of ongoing population based cervical cancer screening programs. This article aims to present our experience with automated quantitative cytology imaging platform, a reading system with an artificial intelligence that we currently use routinely for cervical cancer screening in Shanxi province.Methods: From 2012-2016 a total of 40 178 women were screened. Women were divided into three groups and each group had two subgroups. Smear and liquid based technique were compared using manual and automated platform.Results: Detection rates of CIN2 + and positive rates of CIN2 were higher in all three groups when automated quantitative cytology platform was used compared with groups where reading was done by the pathologist using conventional microscope. Operator’s costs associated with automated quantitative cytology platform vs. conventional reading using light microscope were compared too. The overall costs of operations based on automated platform were proven to be lower.Conclusion: The use of automated platform and artificial intelligence as a means to overcome the lack of cytotechnologists and pathologists and to implement proper quality control in the large scale population based cervical cancer screening seems very promising.

Breast and Cervical Cancer Screening Disparities Associated with Disability Severity

2014 ◽  
Vol 24 (1) ◽  
pp. e147-e153 ◽  
Author(s):  
Willi Horner-Johnson ◽  
Konrad Dobbertin ◽  
Elena M. Andresen ◽  
Lisa I. Iezzoni
Keyword(s):  
Cervical Cancer ◽  
Cancer Screening ◽  
Cervical Cancer Screening ◽  
Breast And Cervical Cancer ◽  
Disability Severity ◽  
Cancer Screening Disparities

Screen-ABLE: A Mixed-Methods Study on Breast and Cervical Cancer Screening Disparities Among Women With Disabilities

2015 ◽  
Vol 69 (Suppl. 1) ◽  
pp. 6911510131p1 ◽  
Author(s):  
Judy Panko Reis ◽  
Marilyn Martin ◽  
Tom Wilson ◽  
Laura VanPuymbrouck ◽  
Jennifer Beaumonth ◽  
...  
Keyword(s):  
Cervical Cancer ◽  
Mixed Methods ◽  
Cancer Screening ◽  
Cervical Cancer Screening ◽  
Mixed Methods Study ◽  
Women With Disabilities ◽  
Breast And Cervical Cancer ◽  
Cancer Screening Disparities

scholarly journals Advanced Screening Technologies and Their Applications in Gynaecological Cytology: Can It Be a Pyrrhic Victory?

2020 ◽  
pp. 1-3
Author(s):  
Thaís Heinke ◽  
Thaís Heinke ◽  
A.F. Logullo
Keyword(s):  
Artificial Intelligence ◽  
Cervical Cancer ◽  
Cancer Screening ◽  
Cervical Cancer Screening ◽  
Ethical Issues ◽  
Population Based ◽  
Improve Accuracy ◽  
Diagnostic Medicine ◽  
The Impact ◽  
Pyrrhic Victory

The impact of artificial intelligence (AI) is already affecting cytopathology on diagnostic medicine, which offers a great perspective and many attractive approches for it. But, even though it may indeed improve accuracy and enhance many processes, the study aims to highlight some additional challenges and ethical issues that are relevant as well. Also, it points out the role AI can play as a strategy to improve cytology practice and teaching worldwide, aiming to obtain best possible performance in population‐based cervical cancer screening according to the different scenarios we can find, and to have the best strategy that may vary accordingly to were it is to be implemented.

scholarly journals Study protocol for a two-site clinical trial to validate a smartphone-based artificial intelligence classifier identifying cervical precancer and cancer in HPV-positive women in Cameroon

PLoS ONE ◽  
2021 ◽  
Vol 16 (12) ◽  
pp. e0260776
Author(s):  
Inès Baleydier ◽  
Pierre Vassilakos ◽  
Roser Viñals ◽  
Ania Wisniak ◽  
Bruno Kenfack ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Cervical Cancer ◽  
Acetic Acid ◽  
Cancer Screening ◽  
Cervical Cancer Screening ◽  
Study Protocol ◽  
Screening Program ◽  
Histopathological Examination ◽  
Current Standard ◽  
Detection Techniques

Introduction Cervical cancer remains a major public health challenge in low- and middle-income countries (LMICs) due to financial and logistical issues. WHO recommendation for cervical cancer screening in LMICs includes HPV testing as primary screening followed by visual inspection with acetic acid (VIA) and treatment. However, VIA is a subjective procedure dependent on the healthcare provider’s experience. Its accuracy can be improved by computer-aided detection techniques. Our aim is to assess the performance of a smartphone-based Automated VIA Classifier (AVC) relying on Artificial Intelligence to discriminate precancerous and cancerous lesions from normal cervical tissue. Methods The AVC study will be nested in an ongoing cervical cancer screening program called “3T-study” (for Test, Triage and Treat), including HPV self-sampling followed by VIA triage and treatment if needed. After application of acetic acid on the cervix, precancerous and cancerous cells whiten more rapidly than non-cancerous ones and their whiteness persists stronger overtime. The AVC relies on this key feature to determine whether the cervix is suspect for precancer or cancer. In order to train and validate the AVC, 6000 women aged 30 to 49 years meeting the inclusion criteria will be recruited on a voluntary basis, with an estimated 100 CIN2+, calculated using a confidence level of 95% and an estimated sensitivity of 90% +/-7% precision on either side. Diagnostic test performance of AVC test and two current standard tests (VIA and cytology) used routinely for triage will be evaluated and compared. Histopathological examination will serve as reference standard. Participants’ and providers’ acceptability of the technology will also be assessed. The study protocol was registered under ClinicalTrials.gov (number NCT04859530). Expected results The study will determine whether AVC test can be an effective method for cervical cancer screening in LMICs.

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