AIMC Topic: Retinal Diseases

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The retina revolution: signaling pathway therapies, genetic therapies, mitochondrial therapies, artificial intelligence.

Current opinion in ophthalmology
PURPOSE OF REVIEW: The aim of this article is to review and discuss the history, current state, and future implications of promising biomedical offerings in the field of retina.

Recent developments in pediatric retina.

Current opinion in ophthalmology
PURPOSE OF REVIEW: Pediatric retina is an exciting, but also challenging field, where patient age and cooperation can limit ease of diagnosis of a broad range of congenital and acquired diseases, inherited retinal degenerations are mostly untreatable...

Future Vision 2020 and Beyond-5 Critical Trends in Eye Research.

Asia-Pacific journal of ophthalmology (Philadelphia, Pa.)
Ophthalmology has been at the forefront of many innovations in basic science and clinical research. The randomized prospective multicenter clinical trial, comparative clinical trials, the bench to beside development of diagnostic and therapeutic devi...

An FP's guide to AI-enabled clinical decision support.

The Journal of family practice
To better understand the capabilities and challenges of artificial intelligence and machine learning, we look at the role they can play in screening for retinopathy and colon cancer.

Depthwise Separable Convolutional Neural Network Model for Intra-Retinal Cyst Segmentation.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Intra-retinal cysts (IRCs) are significant in detecting several ocular and retinal pathologies. Segmentation and quantification of IRCs from optical coherence tomography (OCT) scans is a challenging task due to present of speckle noise and scan inten...

Demystifying the Jargon: The Bridge between Ophthalmology and Artificial Intelligence.

Ophthalmology. Retina
Publications related to artificial intelligence (AI) and machine learning have risen exponentially in the past 5 years in the medical literature, including a number of articles involving retinal disease. The mathematical theories beneath machine lear...

Learning from Everyday Images Enables Expert-like Diagnosis of Retinal Diseases.

Cell
Kermany et al. report an application of a neural network trained on millions of everyday images to a database of thousands of retinal tomography images that they gathered and expert labeled, resulting in a rapid and accurate diagnosis of retinal dise...