Application of Huawei Cloud ModelArts-driven AI-assisted diagnostic system in detecting atypical cervical cytology
- VernacularTitle:华为云ModelArts平台驱动的AI辅助诊断系统在宫颈液基细胞学非典型病变检出中的应用研究
- Author:
Yongqin WEN
1
;
Ruoyu ZHANG
;
Xianlei LI
;
Hua XU
;
Yongqiang XU
Author Information
- Keywords: cervical cancer; liquid-based cytology(LBC); atypical squamous cell; deep learning; Huawei Cloud Model Arts; innovative application; assisted diagnosis
- From: Journal of Xi'an Jiaotong University(Medical Sciences) 2024;45(5):851-858
- CountryChina
- Language:Chinese
- Abstract: Objective To explore and validate the application value of a deep learning model based on the Huawei Cloud ModelArts platform in the diagnosis of atypical cervical cells in liquid-based cytology(LBC)and to evaluate its assistive effect for pathologists with different diagnostic experiences.Methods We retrospectively analyzed 1 044 cervical cytology specimens from Dongguan People's Hospital in 2020.The artifical intelligence(AI)-assisted diagnostic system developed on the Huawei Cloud ModelArts platform was compared with junior,intermediate,and senior pathologists for diagnosis.Sensitivity,specificity,precision,recall,and area under the receiver operating characteristic curve(AUC)were calculated to assess the diagnostic performance of the Al system and its assistive effect for pathologists with different levels of experience.The McNemar test was used to compare the differences between the Al system and manual diagnosis.P＜0.05 was considered statistically significant.Results For the 1 044 cervical exfoliated cytology specimens,the sensitivity and specificity of the AI system in detecting atypical cells was 98.96％and 89.15％,both of which were higher than those of junior doctors(81.95％and 91.81％,respectively).The overall diagnostic accuracy of the Al system was 93.68％,which was significantly higher than that of junior doctors(87.26％,P＜0.001).Al assistance could significantly improve junior doctors'ability to detect atypical cells,with the sensitivity and specificity increasing from 80.1％to 96.5％and from 85.6％to 92.3％,respectively.Conclusion The AI-assisted cervical cytology diagnostic system developed in this study demonstrated superior performance,particularly in significantly improving the diagnostic level of junior pathologists,showing promising clinical application prospects.
