Application value of artificial intelligence-assisted diagnosis in cervical liquid-based cytology screening
LI Ting
LI Qing
QIANG Xian
WANG Haizhen
Abstract：Objective To explore the application value of artificial intelligence(AI)-assisted diagnosis in cervical liquid-based cytology screening.Methods A total of 97,201 cervical cytology samples were collected from the cervical cancer screening program conducted at Changzhou Maternal and Child Health Hospital from January 2024 to August 2025.After preparing liquid-based thin-layer cytology slides,the slides were digitally scanned and analyzed using an AI-assisted diagnostic system.The 2022 version of The Bethesda System(TBS)for cervical cytology reporting was adopted as the diagnostic standard.Atypical squamous cells of undetermined significance(ASC-US)and higher-grade lesions were defined as positive.The sensitivity,specificity,false-negative rate,and false-positive rate of AI-assisted diagnosis and manual screening were evaluated.Results The success rate of AI-assisted diagnosis in this large-scale cervical cancer screening was 99.91%(97,114/97,201).Compared with manual screening,AI demonstrated strong diagnostic agreement across categories:98.99%(8,913/9,004)in NILM,84.32%(3,751/4,449)in ASCUS,87.58%(213/244)in ASC-H,80.58%(1,282/1,591)in LSIL,97.06%(324/334)in HISL,100%(6/6)in SCC,and 68.59%(142/207)in glandular abnormalities.The overall concordance was excellent(Kappa coefficient>0.800).For cervical cancer screening,AI-assisted diagnosis achieved a sensitivity of 94.51%,specificity of 99.10%,positive predictive value(PPV)of 87.42%,and negative predictive value(NPV)of 99.63%,indicating good performance as a screening tool.Conclusion AI-assisted diagnosis demonstrates strong concordance with manual screening in cervical cancer detection.The combination of AI-assisted diagnosis and manual review significantly improves the sensitivity and specificity of cervical liquid-based cytology screening,reduces the risk of missed diagnoses,and greatly enhances diagnostic efficiency.In large-scale cervical cancer screening programs,the combination of AI-assisted diagnostic system and manual review has improved slide-reading efficiency by 3 to 6 times,demonstrating significant advantages in workflow optimization.
Keywords：Liquid-based cytology(LBC)Cervical cancer screeningAI-assisted diagnosis
Publication Date：2025-12-28
Online Publishing Date：2026-01-28(First online date of this platform, not the publication date of the document)
Pages：5( 1555-1559 )