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This paper is in the following e-collection/theme issue:

Public (e)Health, Digital Epidemiology and Public Health Informatics (1121) Demographics of Users, Social & Digital Divide (981) Cost-Effectiveness and Economics (380) mHealth for Screening (311) Innovations and Technology in Cancer Care (574) Innovations and Technology for Cancer Prevention and Screening (213) Artificial Intelligence (2385) Computer-Aided Diagnosis (281) Medical imaging (137) Theme Issue 2025: Artificial Intelligence in Oncology (11)

Published on in Vol 26 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/51477, first published .
Performance of a Full-Coverage Cervical Cancer Screening Program Using on an Artificial Intelligence– and Cloud-Based Diagnostic System: Observational Study of an Ultralarge Population

Performance of a Full-Coverage Cervical Cancer Screening Program Using on an Artificial Intelligence– and Cloud-Based Diagnostic System: Observational Study of an Ultralarge Population

Performance of a Full-Coverage Cervical Cancer Screening Program Using on an Artificial Intelligence– and Cloud-Based Diagnostic System: Observational Study of an Ultralarge Population

Authors of this article:

Lu Ji1 Author Orcid Image ;   Yifan Yao1 Author Orcid Image ;   Dandan Yu2 Author Orcid Image ;   Wen Chen1 Author Orcid Image ;   Shanshan Yin1 Author Orcid Image ;   Yun Fu3 Author Orcid Image ;   Shangfeng Tang1 Author Orcid Image ;   Lan Yao1 Author Orcid Image
Article Authors Cited by (7) Tweetations Metrics

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  1. Abrar S, Isa S, Hairon S, Ismail M, Kadir M. Recent advances in applications of machine learning in cervical cancer research: a focus on prediction models. Obstetrics & Gynecology Science 2025;68(4):247 View
  2. Taha R, Zain El Abdin H, Musleh T. Comparative Analysis of Supervised Machine Learning Models for PCOS Prediction Using Clinical Data. Journal of Engineering Research and Sciences 2025;4(06):16 View
  3. Linder N, Nyirenda D, Mårtensson A, Kaingu H, Ngasala B, Lundin J. AI supported diagnostic innovations for impact in global women’s health. BMJ 2025;391:e086009 View
  4. Wang X, Wang Q, Ding G, Wang J, Tang Y, Feng Y. Artificial intelligence for colposcopic and cytological image analysis in early cervical cancer detection. iScience 2026;29(2):114627 View
  5. Ji L, Zhou X, Yao L. 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 2026;28:e75372 View
  6. Qiao H, Zhao S, Mou H, Guo Y, Fan C, Liu J. A Study on the Application of an AI Image Recognition-Based Early Cervical Cancer Screening System. Health 2025;17(09):1058 View
  7. Li Y, Ji L, Hou X, Tang K, Louw Q, Lundin J, Yao L, Chen S. Artificial intelligence-assisted cervical cancer screening for 9 million women in China. The Lancet Primary Care 2026;2(3):100149 View