ArticleJournal of oncology2022
The Performance of Artificial Intelligence in Cervical Colposcopy: A Retrospective Data Analysis.
Article in Journal of oncology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 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
9 citing papers in PubMed, 16 citations in OpenAlex.
- Article
- Supporting the global reduction of cervical cancer: challenges in colposcopy practice and training.Frontiers in oncology · 2025Review
- Artificial intelligence in atrial fibrillation: emerging applications, research directions and ethical considerations.Frontiers in cardiovascular medicine · 2025Review
- Status quo and future directions of digitalization in gynecology and obstetrics in Germany: a survey of the commission Digital Medicine of the German Society for Gynecology and Obstetrics.Archives of gynecology and obstetrics · 2024Article
- Automated Assessment of Digital Images of Uterine Cervix Captured Using Transvaginal Device-A Pilot Study.Diagnostics (Basel, Switzerland) · 2023Article
- Application of EfficientNet-B0 and GRU-based deep learning on classifying the colposcopy diagnosis of precancerous cervical lesions.Cancer medicine · 2023Article
- Artificial intelligence in colposcopic examination: A promising tool to assist junior colposcopists.Frontiers in medicine · 2023Article
- Cervical Cancer Prophylaxis-State-of-the-Art and Perspectives.Healthcare (Basel, Switzerland) · 2022Review
- Review of the Standard and Advanced Screening, Staging Systems and Treatment Modalities for Cervical Cancer.Cancers · 2022Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveWe aimed to evaluate the performance of artificial intelligence (AI) system in detecting high-grade precancerous lesions.
methodsA retrospective and diagnostic study was conducted in Chongqing Cancer Hospital. Anonymized medical records with cytology, HPV testing, colposcopy findings with images, and the histopathological results were selected. The sensitivity, specificity, and areas under the curve (AUC) in detecting CIN2+ and CIN3+ were evaluated for the AI system, the AI-assisted colposcopy, and the human colposcopists, respectively.
resultsAnonymized medical records from 346 women were obtained. The images captured under colposcopy of 194 women were found positive by the AI system; 245 women were found positive either by human colposcopists or the AI system. In detecting CIN2+, the AI-assisted colposcopy significantly increased the sensitivity (96.6% vs. 88.8%,
conclusionsThe AI system provided equally matched sensitivity to human colposcopists in detecting CIN2+ and CIN3+. The AI-assisted colposcopy significantly improved the sensitivity in detecting CIN2+.
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.