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.

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.

Application of artificial intelligence-based dual-modality analysis combining fundus photography and optical coherence tomography in diabetic retinopathy screening in a community hospital.

Background: To assess the feasibility and clinical utility of artificial intelligence (AI)-based screening for diabetic retinopathy (DR) and macular edema (ME) by combining fundus photos and optical coherence tomography (OCT) images in a community hospital.

Methods: Fundus photos and OCT images were taken for 600 diabetic patients in a community hospital. Ophthalmologists graded these fundus photos according to the International Clinical Diabetic Retinopathy (ICDR) Severity Scale as the ground truth.

Artificial intelligence-based screening for diabetic retinopathy at community hospital.

Objectives: The purpose of this study is to assess the accuracy of artificial intelligence (AI)-based screening for diabetic retinopathy (DR) and to explore the feasibility of applying AI-based technique to community hospital for DR screening.

Methods: Nonmydriatic fundus photos were taken for 889 diabetic patients who were screened in community hospital clinic. According to DR international classification standards, ophthalmologists and AI identified and classified these fundus photos.

[Detection of macular foveal by optical coherence tomography and its influence on results of measurement of central retina thickness].

Objective: To detect macular foveal by Cirrus(TM) HD-OCT using the post acquisition fovea detection and to study its influence on the results of measurement of central retina thickness (CRT).

Methods: In this retrospectively studies, the 512×128 cube scans from 50 eyes of normal subjects and 50 eyes of macular edema patients were analyzed. Three methods for the foveal detection were used, the scan center (SC), the automated detected foveal (AF) and the manually identified foveal (MF).

Functional recovery after intravitreal bevacizumab treatments for idiopathic choroidal neovascularization in young adults.

Purpose: To evaluate the morphology and functional recovery of the retina after treatment of idiopathic choroidal neovascularization using intravitreal injections of bevacizumab in young adults.

Methods: For this interventional case series, 20 eyes of 19 patients with idiopathic choroidal neovascularization were treated with multiple intravitreal injections of bevacizumab. Changes in best-corrected visual acuity before the treatment and at follow-up visits were recorded.