AI Medical Compendium Topic

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Retinal Diseases

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A MULTITASK DEEP-LEARNING SYSTEM FOR ASSESSMENT OF DIABETIC MACULAR ISCHEMIA ON OPTICAL COHERENCE TOMOGRAPHY ANGIOGRAPHY IMAGES.

Retina (Philadelphia, Pa.)
PURPOSE: We aimed to develop and test a deep-learning system to perform image quality and diabetic macular ischemia (DMI) assessment on optical coherence tomography angiography (OCTA) images.

ANALYSIS OF TRANSFER LEARNING FOR SELECT RETINAL DISEASE CLASSIFICATION.

Retina (Philadelphia, Pa.)
PURPOSE: To analyze the effect of transfer learning for classification of diabetic retinopathy (DR) by fundus photography and select retinal diseases by spectral domain optical coherence tomography (SD-OCT).

An Efficient Deep Learning Network for Automatic Detection of Neovascularization in Color Fundus Images.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Retinopathy screening is a non-invasive method to collect retinal images and neovascularization detection from retinal images plays a significant role on the identification and classification of diabetes retinopathy. In this paper, an efficient deep ...

Application of Comprehensive Artificial intelligence Retinal Expert (CARE) system: a national real-world evidence study.

The Lancet. Digital health
BACKGROUND: Medical artificial intelligence (AI) has entered the clinical implementation phase, although real-world performance of deep-learning systems (DLSs) for screening fundus disease remains unsatisfactory. Our study aimed to train a clinically...

Multiclass retinal disease classification and lesion segmentation in OCT B-scan images using cascaded convolutional networks.

Applied optics
Disease classification and lesion segmentation of retinal optical coherence tomography images play important roles in ophthalmic computer-aided diagnosis. However, existing methods achieve the two tasks separately, which is insufficient for clinical ...

Delivering personalized medicine in retinal care: from artificial intelligence algorithms to clinical application.

Current opinion in ophthalmology
PURPOSE OF REVIEW: To review the current status of artificial intelligence systems in ophthalmology and highlight the steps required for clinical translation of artificial intelligence into personalized health care (PHC) in retinal disease.

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...