The artificial intelligence-assisted cytology diagnostic system in large-scale cervical cancer screening: A population-based cohort study of 0.7 million women.

Cancer Medicine
Heling BaoLinhong Wang

Abstract

Adequate 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. We 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+). Finally, 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 (Ptrend  < 0.001). General estimated equations showed that detection of CIN2+ among women with ASC-H or HSIL by AI were significantly h...Continue Reading

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Citations

Feb 3, 2021·Laboratory Investigation; a Journal of Technical Methods and Pathology·Jing KeFusong Jiang
Nov 25, 2020·Life·Andreas C Chrysostomou, Leondios G Kostrikis
May 12, 2021·The Journal of Obstetrics and Gynaecology Research·Kenbun SoneYutaka Osuga

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Methods Mentioned

BETA
and
biopsy
biopsies
genotyping

Software Mentioned

R
ggplot
Landing CytoScanner
SAS
MAVARIC

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