Latest AI and machine learning research in ophthalmology for healthcare professionals.
Explainable AI (XAI) methods provide explanations of AI models, but our understanding of how they compare with human explanations remains limited. Here, we examined human participants' attention strategies when classifying images and when explaining how they classified the images through eye-tracking and compared their attention strategies with saliency-based explanations from current XAI methods....
The rapid development of computer vision technologies and applications has brought forth a range of social and ethical challenges. Due to the unique characteristics of visual technology in terms of data modalities and application scenarios, computer vision poses specific ethical issues. However, the majority of existing literature either addresses artificial intelligence as a whole or pays particu...
Diabetic retinopathy (DR) is a major complication of diabetes mellitus and is a leading cause of vision loss globally. A prompt and accurate diagnosis...
Retinal diseases are among nowadays major public health issues, deservedly needing advanced computer-aided diagnosis. We propose a hybrid model for mu...
Accurate segmentation of retinal vessels in fundus images is of great importance for the diagnosis of numerous ocular diseases. However, due to the co...
As one of the effective ways of ocular disease recognition, early fundus screening can help patients avoid unrecoverable blindness. Although deep lear...
Machine learning (ML) has revolutionized medical image-based diagnostics. In this review, we cover a rapidly emerging field that can be potentially si...
Age-related macular degeneration (AMD) is an eye disease that leads to the deterioration of the central vision area of the eye and can gradually resul...
The transformative role of artificial intelligence (AI) in various fields highlights the need for it to be both accurate and fair. Biased medical AI s...
Hyperlipidemia has many ocular manifestations, the most prevalent being retinal vascular occlusion. Hyperlipidemic lesions and occlusions to the vesse...
Accurate, and objective diagnosis of brain injury remains challenging. This study evaluated useability and reliability of computerized eye-tracker ass...
Thyroid-associated ophthalmopathy (TAO) is a significant autoimmune eye disease known for causing exophthalmos and substantial optic nerve damage. Pri...
Unit activity in particular deep neural networks (DNNs) are remarkably similar to the neuronal population responses to static images along the primate...
Early in life and without special training, human beings discern resemblance between abstract visual stimuli, such as drawings, and the real-world obj...
Autoimmune uveitis, a severe inflammatory condition of the eye, poses significant challenges due to its complex pathophysiology and the critical balan...
Neuromorphic vision sensors or event cameras have made the visual perception of extremely low reaction time possible, opening new avenues for high-dyn...
BACKGROUND AND OBJECTIVES: Optical coherence tomography (OCT) has ushered in a transformative era in the domain of ophthalmology, offering non-invasiv...
Emotion recognition has become increasingly important in the field of Deep Learning (DL) and computer vision due to its broad applicability by using h...
BACKGROUND: Diabetic retinopathy (DR) is one of the most common complications of diabetes mellitus. The global burden is immense with a worldwide prev...
Image-based artificial intelligence (AI) systems stand as the major modality for evaluating ophthalmic conditions. However, most of the currently avai...