RT Journal Article
SR Electronic
T1 Application of artificial intelligence system for screening multiple fundus diseases in Chinese primary healthcare settings: a real-world, multicentre and cross-sectional study of 4795 cases
JF British Journal of Ophthalmology
JO Br J Ophthalmol
FD BMJ Publishing Group Ltd.
SP bjo-2022-322940
DO 10.1136/bjo-2022-322940
A1 Chufeng Gu
A1 Yujie Wang
A1 Yan Jiang
A1 Feiping Xu
A1 Shasha Wang
A1 Rui Liu
A1 Wen Yuan
A1 Nurbiyimu Abudureyimu
A1 Ying Wang
A1 Yulan Lu
A1 Xiaolong Li
A1 Tao Wu
A1 Li Dong
A1 Yuzhong Chen
A1 Bin Wang
A1 Yuncheng Zhang
A1 Wen Bin Wei
A1 Qinghua Qiu
A1 Zhi Zheng
A1 Deng Liu
A1 Jili Chen
YR 2023
UL http://bjo.bmj.com/content/early/2023/03/05/bjo-2022-322940.abstract
AB Background/aims This study evaluates the performance of the Airdoc retinal artificial intelligence system (ARAS) for detecting multiple fundus diseases in real-world scenarios in primary healthcare settings and investigates the fundus disease spectrum based on ARAS.Methods This real-world, multicentre, cross-sectional study was conducted in Shanghai and Xinjiang, China. Six primary healthcare settings were included in this study. Colour fundus photographs were taken and graded by ARAS and retinal specialists. The performance of ARAS is described by its accuracy, sensitivity, specificity and positive and negative predictive values. The spectrum of fundus diseases in primary healthcare settings has also been investigated.Results A total of 4795 participants were included. The median age was 57.0 (IQR 39.0–66.0) years, and 3175 (66.2%) participants were female. The accuracy, specificity and negative predictive value of ARAS for detecting normal fundus and 14 retinal abnormalities were high, whereas the sensitivity and positive predictive value varied in detecting different abnormalities. The proportion of retinal drusen, pathological myopia and glaucomatous optic neuropathy was significantly higher in Shanghai than in Xinjiang. Moreover, the percentages of referable diabetic retinopathy, retinal vein occlusion and macular oedema in middle-aged and elderly people in Xinjiang were significantly higher than in Shanghai.Conclusion This study demonstrated the dependability of ARAS for detecting multiple retinal diseases in primary healthcare settings. Implementing the AI-assisted fundus disease screening system in primary healthcare settings might be beneficial in reducing regional disparities in medical resources. However, the ARAS algorithm must be improved to achieve better performance.Trial registration number NCT04592068.Data are available on reasonable request.