Application of artificial intelligence reading label system in diabetic retinopathy grading training of junior ophthalmologists and medical students
10.3760/cma.j.cn431274-20201025-01445
- VernacularTitle:人工智能阅片标注系统在低年资眼科医师及医学生糖尿病视网膜病变阅片培训中的应用
- Author:
Ruoan HAN
;
Weihong YU
;
Huan CHEN
;
Mingyue LUO
;
Youxin CHEN
- From:
Journal of Chinese Physician
2021;23(5):650-653
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To evaluate the efficiency of using artificial intelligence reading label system in diabetic retinopathy (DR) grading training among junior ophthalmologists and medical students.Methods:520 diabetic fundus images were randomly divided into 8 groups with 65 images in each group. 13 junior ophthalmologists and medical students were selected as the research objects. Each of them read 8 groups of pictures and evaluated the DR grading of each fundus image. The sensitivity, specificity and diagnostic test consistency (Q-kappa value) of grading results were analyzed with the DR grading given by 3 senior ophthalmologists as the gold standard. The average Q-kappa values of 13 subjects were compared between the first four times and the last four times.Results:Through 8 round reading, the average Q-kappa was elevated from 0.67 to 0.81. Average Q-kappa of round 1 to 4 was 0.77, and average Q-kappa of round 5 to 8 was 0.81. The participants were divided into two groups. Participants in group 1 were junior ophthalmologists and participants in group 2 were medical students. Average Q-kappa of group 1 was elevated from 0.71 to 0.76. Average Q-kappa of group 2 was elevated from 0.63 to 0.84.Conclusions:The artificial intelligence reading label system was a useful tool in training junior ophthalmologists and medical students in doing diabetic retinopathy grading.
