Latest AI and machine learning research in ophthalmology for healthcare professionals.
There is an increasing need to integrate multimodal datasets in epilepsy research, particularly to correlate electrophysiology with imaging in patients with refractory epilepsy. We present a multimodal paired 3T and 7T MRI dataset acquired from 30 drug-resistant focal epilepsy patients (18 females, 38.8 ± 11.7 years) who underwent T1-weighted (T1w), T2-weighted (T2w), Fluid Attenuated Inversion Re...
To evaluate the orthokeratology (ortho-K) lens fitting and visual quality of artificial intelligence (AI) -fitted personalized lenses in myopic children with corneal asymmetry.This retrospective study included 139 children with corneal asymmetry who underwent ortho-K fitting, grouped according to conventional vision shaping treatment (VST) lenses (n = 53), corneal refractive therapy (CRT) lenses (...
BACKGROUND: Artificial intelligence (AI) has rapidly advanced in surgical applications. However, existing single-modality AI models relying solely on ...
In low-resource clinical settings, Plasmodium falciparum infection and hypoglycemia frequently co-present yet require discrete diagnostic platforms, c...
Artificial intelligence (AI) technologies such as machine learning (ML), deep learning (DL), predictive analytics and other tools are rapidly changing...
Birdshot chorioretinitis is a rare uveitis where research is limited by the lack of large, publicly available imaging datasets. To address this gap, w...
Proteomics represents a powerful but underutilized approach for characterizing eye aging. Here, leveraging data from three large-scale, cross-national...
BACKGROUND: Early identification of autism spectrum disorder (ASD) is essential for improving developmental outcomes but remains challenging due to di...
Conventional frame-based vision systems inevitably generate large amounts of redundant data owing to the continuous capture of absolute light intensit...
UNLABELLED: This study presents a fast, lightweight computer vision framework that achieves high accuracy in verifying the correct use of goggles and ...
PURPOSE: Large language models (LLMs) are increasingly integrated into radiology workflows, but their demographic biases have not been evaluated in di...
OBJECTIVE: Manual segmentation of the whole anterior visual pathway (aVP) from high-resolution magnetic resonance imaging (MRI) is time-consuming and ...
Chromovitrectomy has revolutionized vitreoretinal surgery by enabling the visualization of nearly transparent intraocular structures. This review eval...
Current psychiatric diagnoses lack objective criteria, and this study aims to evaluate EEM as a potential tool for improving diagnostic objectivity ac...
BACKGROUND: Clinical medicine postgraduates are expected to attain competencies equivalent to senior resident physicians. However, ophthalmology gradu...
Eye tracking during visual search generates spatiotemporally rich but complex data. Traditional analyses often utilize simplified metrics (saccade lan...
IMPORTANCE: Ocular surface malignancies pose risks to vision and survival yet are frequently misdiagnosed as benign lesions because of their subtle pr...
AIMS: To identify early oculomic biomarkers predictive of pathologic myopia (PM) in children with high myopia (HM) and to develop an artificial intell...
Plant-based diets may influence age-related eye diseases (AREDs), but whether ocular benefits depend on diet quality remains unclear. We examined asso...