Screening And Detecting Eye Diseases With Hybrid Deep Learning Algorithms From Fundus Images And Validation Of Automated Artificial Intelligence Algorithm
Trial ID: NCT06213896
Status: COMPLETED
Study type: OBSERVATIONAL
Start date: 2023-03-01
Completion date: 2024-04-18
Sponsor: Ural Telekomunikasyon Sanayi Ticaret Anonim Sirketi
Conditions: Glaucoma; Age-Related Macular Degeneration; Retinal Vein Occlusion; Diabetic Retinopathy; Diabetic Macular Edema; Eye Diseases
Interventions: Mydriatic Agent; Color Fundus Photography; EyeCheckup v2.0
Locations: Akdeniz University Hospital
Countries: Turkey (Türkiye)
Enrollment: 1528
Age range: 18 Years - None
Sex: ALL

Summary:
Eye health is of great importance for quality of life. Some eye diseases can progress and cause permanent damage up to vision loss if they are not treated early. Therefore, it is of great importance to have regular eye examinations and to detect possible eye diseases before they progress. Healthy people should also undergo eye screening once a year, and those with any complaints regarding eye health should be examined.

With the advancing technology, Artificial Intelligence (AI) has begun to play a significant role in the healthcare sector. Retinal diseases, serious health problems resulting from damage to the back part of the eye's retina, include conditions such as retinopathy, macular degeneration, and glaucoma. Artificial intelligence, with its visual recognition and analysis capabilities, holds great potential in the early diagnosis of retinal diseases.

AI-based diagnosis of retinal diseases typically involves the use of specialized algorithms that analyze retinal images. These algorithms identify abnormal features in the eye, providing doctors with a quick and accurate diagnosis.

EyeCheckup v2.0 will diagnose glaucoma suspicion, severe glaucoma suspicion, age-related macular degeneration diagnosis, RVO diagnosis, diabetic retinopathy diagnosis and stage, presence/absence of DME suspicion and other retinal diseases from fundus images. This study is designed to assess the safety and efficacy of EyeCheckup v2.0.

The study is a single center study to determine the sensitivity and specificity of EyeCheckup to retinal and optic disc diseases. EyeCheckup v2.0 is an automated software device that is designed to analyze ocular fundus digital color photographs taken in frontline primary care settings in order to quickly screen.

Eligibility criteria:
Inclusion Criteria:

Must understand the study and sign informed consent. No history of retinal vascular disease, cataracts or any other disease that may affect the appearance of the retina or optic disc (refractive error and ocular surface disease are allowed).

No history of intraocular surgery or ocular laser treatment for any retinal disease, other than cataract surgery.

18 years and over

Exclusion Criteria:

Not understand the study or informed consent, Media opacity or other defect that would prevent taking a fundus photograph with the feature to be evaluated (which could not be taken with a non-mydriatic fundus camera in 6 attempts or was rejected 6 times by the EyeCheckup quality algorithm due to quality), Has intraocular surgery other than cataracts or has had laser treatment on the retina, Contraindicated for imaging with the fundus imaging systems used in the study, Under 18 years

Outcomes:
To determine the accuracy of diagnosis with artificial intelligence algorithm