Consistency analysis of OCT image by artificial intelligence recognition and ophthalmologist's recognition for age-related macular degeneration

Abstract

AIM: To investigate the feasibility of artificial intelligence(AI)in reading retinal optical coherence tomography(OCT)images of age-related macular degeneration(ARMD)in clinic. METHODS: From November 2019 to November 2021, a total of 1 579 OCT images were collected in the outpatient department, and the imaging results of ophthalmologist and AI were collected. The Kappa consistency test of classification results without ARMD and with ARMD were analyzed. RESULTS: The Kappa coefficients of the judgement of ophthalmologists about ARMD was 0.934. The Kappa coefficients between AI and ophthalmologists was 0.738. The sensitivity, specificity and area under curve(AUC)of AI to ARMD were 73.08%, 95.07% and 0.841 respectively. CONCLUSION: AI has a high consistency with ophthalmologists in the recognition of ARMD based on OCT images, which is suitable for primary hospitals to complete the early screening and early referral of ARMD.

Keywords

• age-related macular degeneration
• optical coherence tomography(oct)
• artificial intelligence
• consistency analysis