Ophthalmology

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

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A new era of psoriasis treatment: Drug repurposing through the lens of nanotechnology and machine learning.

Psoriasis is a persistent inflammatory skin disorder characterized by hyper-proliferation and abnorm...

ADFQ-ViT: Activation-Distribution-Friendly post-training Quantization for Vision Transformers.

Vision Transformers (ViTs) have exhibited exceptional performance across diverse computer vision tas...

Machine Learning Techniques for Simulating Human Psychophysical Testing of Low-Resolution Phosphene Face Images in Artificial Vision.

To evaluate the quality of artificial visual percepts generated by emerging methodologies, researche...

Event-driven figure-ground organisation model for the humanoid robot iCub.

Figure-ground organisation is a perceptual grouping mechanism for detecting objects and boundaries, ...

Large-scale benchmarking and boosting transfer learning for medical image analysis.

Transfer learning, particularly fine-tuning models pretrained on photographic images to medical imag...

Standardizing canine breed data in veterinary records is challenging, but computer vision offers an alternative perspective on breed assignment.

Dog breed is fundamental health information, especially in the context of breed-linked diseases. The...

(DA-U)Net: double attention UNet for retinal vessel segmentation.

BACKGROUND: Morphological changes in the retina are crucial and serve as valuable references in the ...

Diagnostic Accuracy of IDX-DR for Detecting Diabetic Retinopathy: A Systematic Review and Meta-Analysis.

PURPOSE: Diabetic retinopathy (DR) is a leading cause of vision loss worldwide, making early detecti...

Use of a Convolutional Neural Network to Predict the Response of Diabetic Macular Edema to Intravitreal Anti-VEGF Treatment: A Pilot Study.

PURPOSE: To utilize a convolutional neural network (CNN) to predict the response of treatment-naïve ...

Reinforcement-based leveraging transfer learning for multiclass optical coherence tomography images classification.

The accurate diagnosis of retinal diseases, such as Diabetic Macular Edema (DME) and Age-related Mac...

The performance of ChatGPT-4 and Bing Chat in frequently asked questions about glaucoma.

PurposeTo evaluate the appropriateness and readability of the responses generated by ChatGPT-4 and B...

Detection of Ocular Surface Squamous Neoplasia Using Artificial Intelligence With Anterior Segment Optical Coherence Tomography.

PURPOSE: To develop and validate a deep learning (DL) model to differentiate ocular surface squamous...

Head-mounted surgical robots are an enabling technology for subretinal injections.

Therapeutic protocols involving subretinal injection, which hold the promise of saving or restoring ...

World and Human Action Models towards gameplay ideation.

Generative artificial intelligence (AI) has the potential to transform creative industries through s...

Artificial intelligence in the diagnosis of uveal melanoma: advances and applications.

Advancements in machine learning and deep learning have the potential to revolutionize the diagnosis...

AI for glaucoma, Are we reporting well? a systematic literature review of DECIDE-AI checklist adherence.

BACKGROUND/OBJECTIVES: This systematic literature review examines the quality of early clinical eval...

Intelligent Verification Tool for Surgical Information of Ophthalmic Patients: A Study Based on Artificial Intelligence Technology.

OBJECTIVE: With the development of day surgery, the characteristics of "short, frequent and fast" op...

HDL-ACO hybrid deep learning and ant colony optimization for ocular optical coherence tomography image classification.

Optical Coherence Tomography (OCT) plays a crucial role in diagnosing ocular diseases, yet conventio...

Enhancing diabetic retinopathy diagnosis: automatic segmentation of hyperreflective foci in OCT via deep learning.

OBJECTIVE: Hyperreflective foci (HRF) are small, punctate lesions ranging from 20 to 50 m and exhib...

Capsule network-based deep learning for early and accurate diabetic retinopathy detection.

Glaucoma, an optic nerve disease resulting in blindness if left untreated, is a difficult condition ...

Artificial intelligence-enhanced retinal imaging as a biomarker for systemic diseases.

Retinal images provide a non-invasive and accessible means to directly visualize human blood vessels...

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