AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Retinal Detachment

Showing 11 to 20 of 20 articles

Clear Filters

Therapeutic response in the HAWK and HARRIER trials using deep learning in retinal fluid volume and compartment analysis.

Eye (London, England)
OBJECTIVES: To assess the therapeutic response to brolucizumab and aflibercept by deep learning/OCT-based analysis of macular fluid volumes in neovascular age-related macular degeneration.

Deep learning for ultra-widefield imaging: a scoping review.

Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie
PURPOSE: This article is a scoping review of published and peer-reviewed articles using deep-learning (DL) applied to ultra-widefield (UWF) imaging. This study provides an overview of the published uses of DL and UWF imaging for the detection of opht...

Development of a deep-learning system for detection of lattice degeneration, retinal breaks, and retinal detachment in tessellated eyes using ultra-wide-field fundus images: a pilot study.

Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie
PURPOSE: To investigate the detection of lattice degeneration, retinal breaks, and retinal detachment in tessellated eyes using ultra-wide-field fundus imaging system (Optos) with convolutional neural network technology.

A Deep Learning Model for Screening Multiple Abnormal Findings in Ophthalmic Ultrasonography (With Video).

Translational vision science & technology
PURPOSE: The purpose of this study was to construct a deep learning system for rapidly and accurately screening retinal detachment (RD), vitreous detachment (VD), and vitreous hemorrhage (VH) in ophthalmic ultrasound in real time.

Predictive modeling of proliferative vitreoretinopathy using automated machine learning by ophthalmologists without coding experience.

Scientific reports
We aimed to assess the feasibility of machine learning (ML) algorithm design to predict proliferative vitreoretinopathy (PVR) by ophthalmologists without coding experience using automated ML (AutoML). The study was a retrospective cohort study of 506...

Deep learning for detecting retinal detachment and discerning macular status using ultra-widefield fundus images.

Communications biology
Retinal detachment can lead to severe visual loss if not treated timely. The early diagnosis of retinal detachment can improve the rate of successful reattachment and the visual results, especially before macular involvement. Manual retinal detachmen...

Accuracy of deep learning, a machine-learning technology, using ultra-wide-field fundus ophthalmoscopy for detecting rhegmatogenous retinal detachment.

Scientific reports
Rhegmatogenous retinal detachment (RRD) is a serious condition that can lead to blindness; however, it is highly treatable with timely and appropriate treatment. Thus, early diagnosis and treatment of RRD is crucial. In this study, we applied deep le...

Cooperative robot assistant for vitreoretinal microsurgery: development of the RVRMS and feasibility studies in an animal model.

Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie
PURPOSE: The purpose of the study was to describe the development of a robotic aided surgical system named RVRMS (robotic vitreous retinal microsurgery system) and to evaluate the capability for using it to perform vitreoretinal surgery.