Ophthalmology

Latest AI and machine learning research in ophthalmology for healthcare professionals.

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Validation of neuron activation patterns for artificial intelligence models in oculomics.

Recent advancements in artificial intelligence (AI) have prompted researchers to expand into the fie...

Leveraging deep learning and computer vision technologies to enhance management of coastal fisheries in the Pacific region.

This paper presents the design and development of a coastal fisheries monitoring system that harness...

Integrating AI with tele-ophthalmology in Canada: a review.

The field of ophthalmology is rapidly advancing, with technological innovations enhancing the diagno...

Predicting Basketball Shot Outcome From Visuomotor Control Data Using Explainable Machine Learning.

Quiet eye (QE), the visual fixation on a target before initiation of a critical action, is associate...

Handling missing data and measurement error for early-onset myopia risk prediction models.

BACKGROUND: Early identification of children at high risk of developing myopia is essential to preve...

Optoelectronic neuron based on transistor combined with volatile threshold switching memristors for neuromorphic computing.

The human perception and learning heavily rely on the visual system, where the retina plays a vital ...

Empowering Portable Age-Related Macular Degeneration Screening: Evaluation of a Deep Learning Algorithm for a Smartphone Fundus Camera.

OBJECTIVES: Despite global research on early detection of age-related macular degeneration (AMD), no...

Comparison review of image classification techniques for early diagnosis of diabetic retinopathy.

Diabetic retinopathy (DR) is one of the leading causes of vision loss in adults and is one of the de...

A Vision Transformer-Based Framework for Knowledge Transfer From Multi-Modal to Mono-Modal Lymphoma Subtyping Models.

Determining lymphoma subtypes is a crucial step for better patient treatment targeting to potentiall...

Deep learning approach for detecting tomato flowers and buds in greenhouses on 3P2R gantry robot.

In recent years, significant advancements have been made in the field of smart greenhouses, particul...

Auxiliary diagnostic method of Parkinson's disease based on eye movement analysis in a virtual reality environment.

Eye movement dysfunction is one of the non-motor symptoms of Parkinson's disease (PD). An accurate a...

Robust mosquito species identification from diverse body and wing images using deep learning.

Mosquito-borne diseases are a major global health threat. Traditional morphological or molecular met...

Impact of acquisition area on deep-learning-based glaucoma detection in different plexuses in OCTA.

Glaucoma is a group of neurodegenerative diseases that can lead to irreversible blindness. Yet, the ...

Comparative analysis of artificial intelligence and expert assessments in detecting neonatal procedural pain.

Assessing pain in newborns in the NICU is crucial due to their frequent exposure to painful stimuli,...

Machine vision-based detection of forbidden elements in the high-speed automatic scrap sorting line.

Highly efficient industrial sorting lines require fast and reliable classification methods. Various ...

Application of Deep Learning Algorithms Based on the Multilayer Y0L0v8 Neural Network to Identify Fungal Keratitis.

UNLABELLED: is to develop a method for diagnosing fungal keratitis based on the analysis of photogr...

Federated Learning in Glaucoma: A Comprehensive Review and Future Perspectives.

CLINICAL RELEVANCE: Glaucoma is a complex eye condition with varied morphological and clinical prese...

Developing Machine Vision in Tree-Fruit Applications-Fruit Count, Fruit Size and Branch Avoidance in Automated Harvesting.

Recent developments in affordable depth imaging hardware and the use of 2D Convolutional Neural Netw...

Optimized deep CNN for detection and classification of diabetic retinopathy and diabetic macular edema.

Diabetic Retinopathy (DR) and Diabetic Macular Edema (DME) are vision related complications prominen...

Prediction of treatment outcome for branch retinal vein occlusion using convolutional neural network-based retinal fluorescein angiography.

Deep learning techniques were used in ophthalmology to develop artificial intelligence (AI) models f...

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