AI Medical Compendium Journal:
Clinical & experimental ophthalmology

Showing 1 to 10 of 21 articles

Deep learning in optical coherence tomography: Where are the gaps?

Clinical & experimental ophthalmology
Optical coherence tomography (OCT) is a non-invasive optical imaging modality, which provides rapid, high-resolution and cross-sectional morphology of macular area and optic nerve head for diagnosis and managing of different eye diseases. However, in...

Efficacy and accuracy of artificial intelligence to overlay multimodal images from different optical instruments in patients with retinitis pigmentosa.

Clinical & experimental ophthalmology
BACKGROUND: Retinitis pigmentosa (RP) represents a group of progressive, genetically heterogenous blinding diseases. Recently, relationships between measures of retinal function and structure are needed to help identify outcome measures or biomarkers...

Randomised controlled trial on robot-assisted versus manual surgery for pucker peeling.

Clinical & experimental ophthalmology
BACKGROUND: The aim was to explore the feasibility and safety of performing common surgical steps in epiretinal membrane (ERM) peeling using the Preceyes Surgical System (PSS).

Automation of dry eye disease quantitative assessment: A review.

Clinical & experimental ophthalmology
Dry eye disease (DED) is a common eye condition worldwide and a primary reason for visits to the ophthalmologist. DED diagnosis is performed through a combination of tests, some of which are unfortunately invasive, non-reproducible and lack accuracy....

Refractive outcomes of second-eye adjustment methods on intraocular lens power calculation in second eye.

Clinical & experimental ophthalmology
BACKGROUND: To investigate the refractive outcomes of second-eye adjustment (SEA) methods in different intraocular lens (IOL) power calculation formulas for second eye following bilateral sequential cataract surgery.

Deep learning versus ophthalmologists for screening for glaucoma on fundus examination: A systematic review and meta-analysis.

Clinical & experimental ophthalmology
BACKGROUND: In this systematic review and meta-analysis, we aimed to compare deep learning versus ophthalmologists in glaucoma diagnosis on fundus examinations.

Emergence of non-artificial intelligence digital health innovations in ophthalmology: A systematic review.

Clinical & experimental ophthalmology
The prominent rise of digital health in ophthalmology is evident in the current age of Industry 4.0. Despite the many facets of digital health, there has been a greater slant in interest and focus on artificial intelligence recently. Other major elem...