ReviewJournal of digital imaging2023
Artificial Intelligence-driven Digital Cytology-based Cervical Cancer Screening: Is the Time Ripe to Adopt This Disruptive Technology in Resource-constrained Settings? A Literature Review.
Review in Journal of digital imaging, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
13 citing papers in PubMed.
- The Practice of Cytopathology in India: Insights From a 2025 Nationwide Survey.Diagnostic cytopathology · 2026Article
- Artificial Intelligence in Cervical Cytology: Opportunities and Limitations in Screening, Triage, and Diagnostic Support.Diagnostics (Basel, Switzerland) · 2026Review
- Hyperspectral Imaging of Whole-Cell Region for Differentiating Cervical Squamous Intraepithelial Lesion Cytology.Cancer medicine · 2026Article
- Development and interpretability of an XGBoost model to predict high grade cervical intraepithelial neoplasia.BMC medical informatics and decision making · 2026Article
- Application and prospect of artificial intelligence in diagnostic imaging of prostate cancer.NPJ digital medicine · 2026Review
- Artificial Intelligence in Veterinary Clinical Pathology-An Introduction and Review.Veterinary clinical pathology · 2025Review
- [TruScreen Combined With High-Risk Human Papillomavirus Testing vs Thinprep Cytology Test Combined With High-Risk Human Papillomavirus Testing for Cervical Cancer Screening: A Comparative Clinical Study].Sichuan da xue xue bao. Yi xue ban = Journal of Sichuan University. Medical science edition · 2025Article
- Analysis of the sensitivity of high-grade squamous intraepithelial lesion Pap diagnosis and interobserver variability with the Hologic Genius Digital Diagnostics System.Cancer cytopathology · 2025Article
- Artificial intelligence strengthens cervical cancer screening - present and future.Cancer biology & medicine · 2024Review
- Performance of Human Gene EPB41L3 and HPV 16/18 Viral DNA Methylation to Triage hrHPV-Positive Women.Vaccines · 2023Article
- AI-assisted system improves the work efficiency of cytologists via excluding cytology-negative slides and accelerating the slide interpretation.Frontiers in oncology · 2023Article
- Application of artificial intelligence in gynecologic cancers: A bibliometric analysis.Digital healthArticle
- The Application of Artificial Intelligence to Cancer Research: A Comprehensive Guide.Technology in cancer research & treatmentReview
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Cervical cancer is still a public health scourge in the developing countries due to the lack of organized screening programs. Though liquid-based cytology methods improved the performance of cervical cytology, the interpretation still suffers from subjectivity. Artificial intelligence (AI) algorithms have offered objectivity leading to better sensitivity and specificity of cervical cancer screening. Whole slide imaging (WSI) that converts a glass slide to a virtual slide provides a new perspective to the application of AI, especially for cervical cytology. In the recent years, there have been a few studies employing various AI algorithms on WSI images of conventional or LBC smears and demonstrating differing sensitivity/specificity or accuracy at detection of abnormalities in cervical smears. Considering the interest in AI-based screening modalities, this well-timed review intends to summarize the progress in this field while highlighting the research gaps and providing future research directions.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.