ArticleCancer medicine2020
The artificial intelligence-assisted cytology diagnostic system in large-scale cervical cancer screening: A population-based cohort study of 0.7 million women.
Article in Cancer medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 48 papers, 1 of them a synthesis that pooled it.
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Who cites it
48 citing papers in PubMed, 1 synthesis or guideline pooled it, 99 citations in OpenAlex.
- Artificial intelligence in cytopathological applications for cancer: a review of accuracy and analytic validity.European journal of medical research · 2024Pooled it
- From HPV infection to cervical precancer: Molecular mechanisms, immune microenvironment and emerging technologies.Cellular and molecular life sciences : CMLS · 2026Review
- 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
- Factors Influencing Universal Coverage of AI-Assisted Cervical Cancer Screening: Qualitative Study Based on the Macro Model of Health System.Journal of medical Internet research · 2026Article
- Article
- Quantitative Texture Analysis of Cervical Cytology Identifies Endometrial Lesions in Atypical Glandular Cells on Liquid-Based Cytology: A Pilot Study.Diagnostics (Basel, Switzerland) · 2026Article
- Use of artificial intelligence in the diagnosis of alterations in cervical cytology: A university population-based observational studyBiomedica : revista del Instituto Nacional de Salud · 2025Observational
- Harnessing artificial intelligence for enhanced veterinary diagnostics: A look to quality assurance, Part I Model development.Veterinary clinical pathology · 2025Review
- Artificial intelligence-driven screening, early diagnosis, and treatment strategies for cervical cancer: an overview.Infectious agents and cancer · 2025Review
- Artificial intelligence in the diagnosis and management of gynecologic cancer.International journal of gynaecology and obstetrics: the official organ of the International Federation of Gynaecology and Obstetrics · 2025Review
- Article
- Is a score enough? Pitfalls and solutions for AI severity scores.European radiology experimental · 2025Article
- Progress in the application research of cervical cancer screening developed by artificial intelligence in large populations.Discover oncology · 2025Review
- Review
- Artificial Intelligence Advancements in Oncology: A Review of Current Trends and Future Directions.Biomedicines · 2025Review
- AI-Based Identification Method for Cervical Transformation Zone Within Digital Colposcopy: Development and Multicenter Validation Study.JMIR cancer · 2025Article
- Research progress of artificial intelligence in the early screening, diagnosis, precise treatment and prognosis prediction of three central gynecological malignancies.Frontiers in oncology · 2025Review
- 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
- A Systematic Review of the Application of Artificial Intelligence in Colposcopy: Diagnostic Accuracy for Cervical Intraepithelial Neoplasia and Cervical Cancer.Clinical Medicine Insights. Oncology · 2025Review
Corrections and comments
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Authors and funding
11 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundAdequate cytology is limited by insufficient cytologists in a large-scale cervical cancer screening. We aimed to develop an artificial intelligence (AI)-assisted cytology system in cervical cancer screening program.
methodsWe conducted a perspective cohort study within a population-based cervical cancer screening program for 0.7 million women, using a validated AI-assisted cytology system. For comparison, cytologists examined all slides classified by AI as abnormal and a randomly selected 10% of normal slides. Each woman with slides classified as abnormal by either AI-assisted or manual reading was diagnosed by colposcopy and biopsy. The outcomes were histologically confirmed cervical intraepithelial neoplasia grade 2 or worse (CIN2+).
resultsFinally, we recruited 703 103 women, of whom 98 549 were independently screened by AI and manual reading. The overall agreement rate between AI and manual reading was 94.7% (95% confidential interval [CI], 94.5%-94.8%), and kappa was 0.92 (0.91-0.92). The detection rates of CIN2+ increased with the severity of cytology abnormality performed by both AI and manual reading (P
conclusionsAI-assisted cytology system could exclude most of normal cytology, and improve sensitivity with clinically equivalent specificity for detection of CIN2+ compared with manual cytology reading. Overall, the results support AI-based cytology system for the primary cervical cancer screening in large-scale population.
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