Automatic detection of 39 fundus diseases and conditions in retinal ...
WEBAug 10, 2021 — Retinal fundus diseases can lead to irreversible visual impairment without timely diagnoses and appropriate treatments. Single disease-based deep learning algorithms had been developed for the...
Artificial Intelligence in Retina - EyeWiki
WEBThe most common application of AI methods in retina is the detection of disease-related features on color fundus photographs. With the advent of OCT in the early 2000s, automated segmentation has been applied to delineate anatomic and pathologic features in retinal diseases.
Artificial Intelligence to Detect Papilledema from Ocular Fundus ...
WEBApr 14, 2020 — We found that an artificial-intelligence, deep-learning algorithm that was trained on ocular fundus photographs had high sensitivity and specificity for discriminating between papilledema...
Retina Fundus Photograph-Based Artificial Intelligence …
WEBJun 24, 2024 — We conducted a systematic review of research in artificial intelligence (AI) for retinal fundus photographic images. We highlighted the use of various AI algorithms, including deep learning (DL) models, for application in ophthalmic and non-ophthalmic (i.e., systemic) disorders.
Artificial intelligence to distinguish retinal vein occlusion patients ...
WEBOct 27, 2022 — We first collected fundus images from the fellow eye of patients with retinal vein occlusion and normal individuals. The fundus images were then pre-processed and used as input to the model.
Application of Comprehensive Artificial intelligence Retinal Expert ...
WEBIn this national real-world evidence study, we trained a DLS, the Comprehensive AI Retinal Expert (CARE) system, to identify the 14 most common retinal abnormalities using 207 228 colour fundus photographs derived from 16 clinical settings with …
A foundation model for generalizable disease detection from retinal ...
WEBSep 13, 2023 — Medical artificial intelligence (AI) offers great potential for recognizing signs of health conditions in retinal images and expediting the diagnosis of eye diseases and systemic disorders 1.
Artificial Intelligence to Identify Retinal Fundus Images, Quality ...
WEBFeb 13, 2020 — Artificial intelligence for determining if a retinal fundus image was assessable or not had an accuracy of 92%, compared to human determination and an AUC of 0.947. This CNN also had high sensitivity (97%) and specificity (82%).
A new handheld fundus camera combined with visual artificial ...
WEBApr 18, 2022 — The handheld Aurora fundus camera combined with autonomous AI system is well-suited in DR screening without mydriasis because of its high sensitivity of DR detection as well as its image quality, but its specificity needs to be improved with better modeling of the data.
Artificial Intelligence for Screening of Multiple Retinal and Optic ...
WEBMay 3, 2022 — Artificial Intelligence for Screening of Multiple Retinal and Optic Nerve Diseases | Ophthalmology | JAMA Network Open | JAMA Network. Table. Baseline Characteristics of Participants and Images in Prospective Screening Dataset. Lancet Glob Health 10.1016/S2214-109X (20)30489-7 PubMed Google Scholar.