Ophthalmology

ECG-Based Prediction of Shock-Refractory Ventricular Fibrillation During Resuscitation Without Interrupting CPR.

Biatrial cardioneuroablation guided by robotic magnetic navigation and artificial intelligence-based mapping in vagal bradyarrhythmias: A controlled observational study.

PURPOSE: Reflex bradyarrhythmias and syncope related to excessive vagal tone may be refractory to conservative therapy and significantly impair quality of life. Cardioneuroablation (CNA) has emerged as a device-sparing alternative, but real-world outcome data remain limited. METHODS: We retrospectively evaluated 12 consecutive patients (aged 23-55 years) with drug-refractory, vagally mediated brad...

Comment on "A deep learning approach for the screening of referable age-related macular degeneration - Model development and external validation".

Diagnostic Accuracy of Artificial Intelligence-Enabled Retinal Biomarkers for Detecting Type 2 Diabetes and Prediabetes Among Asian Indians [DART Study].

PURPOSE: To identify retinal microvascular features that distinguish normoglycemia from diabetes mellitus (DM)[Study-1] and prediabetes (PreDM)[Study-...

On-device single channel EEG classification on Android smartphones using lightweight machine learning models.

OBJECTIVE: Electroencephalogram (EEG) signals capture neuronal activity by measuring electrical activity on the scalp, making them valuable for cognit...

Organotypic Retinal Explant Culture as a Model for Neuroretinal Degenerative Disease and Future Applications.

Organotypic retinal explant cultures are a valuable experimental tool for investigating neuroretinal diseases and advancing therapeutic strategies. Ex...

AI-based prediction of best-corrected visual acuity in patients with multiple retinal diseases using multimodal medical imaging.

BACKGROUND/AIMS: This study evaluated the performance of artificial intelligence (AI) algorithms in predicting best-corrected visual acuity (BCVA) for...

Sleep deprivation and epiretinal membrane risk: Machine learning findings from a nation-wide survey.

PURPOSE: This cross-sectional study explored the association between sleep deprivation and epiretinal membrane (ERM) using machine learning applied to...

Identification of Chlamydia pneumoniae and NLRP3 inflammasome activation in Alzheimer's disease retina.

Chlamydia pneumoniae is an intracellular bacterium implicated in Alzheimer's disease (AD), but its role in retinal pathology and disease progression i...

A systematic review of AI for predicting glaucoma progression: challenges and recommendations towards clinical implementation.

Glaucoma is the leading cause of irreversible blindness worldwide with heterogeneous progression rates. Artificial Intelligence (AI) may enable accura...

A comparative evaluation of parafoveal and perifoveal macular vessel density loss in glaucoma using 3 × 3 mm OCTA scans.

In a prior study we demonstrated the strong performance of convolutional neural networks (CNNs) in distinguishing healthy from glaucomatous eyes and s...

Awareness, trust, and expectations of AI for glaucoma care among Bulgarian ophthalmologists: Role of demographic factors.

Artificial intelligence (AI) holds promise for enhancing glaucoma screening and management, yet its adoption depends on clinician perceptions, particu...

Machine learning-based prediction of diabetic retinopathy from pupillary abnormalities in a South Indian population.

Diabetic retinopathy (DR) is a common complication of diabetes that can lead to vision loss. Early detection and prevention of DR is crucial to reduce...

A Framework for Healthcare from the Eye: Oculomics as a Powerful Window to Systemic Health.

PURPOSE: To present a comprehensive framework for integrating oculomics to assess ocular and systemic health into coordinated health care delivery mod...

Organic neuromorphic vision devices with multilevel memory for palmprint identification.

Neuromorphic visual devices have emerged as a critical strategy to address the limitation of the von Neumann bottleneck. However, the role of interfac...

Study on methods for measuring beef color and predicting storage time based on computer vision.

In this study, a non-destructive and accurate method based on computer vision and machine learning was developed to measure beef surface color and to ...

Generative Artificial Intelligence-Enabled Saliency Analysis of Eye Tracking in Cerebral/Cortical Visual Impairment (SET-CVI).

PURPOSE: Children with cerebral/cortical visual impairment (CVI) have neurological conditions that impact visual pathways in the brain, leading to def...

Localization of the Berger effect in human posterior brain regions with simultaneous electroencephalogram (EEG) and stereo-EEG (SEEG) recordings.

The Berger effect, characterized by a marked increase in alpha power (8-13 Hz) upon eye closure, is a fundamental neurophysiological phenomenon whose ...

Real-Time Characterization of Colonic Polyps: A Multicenter Prospective Study Evaluating the CAD-EYE System in Screening Colonoscopies.

BACKGROUND AND STUDY AIMS: Polypectomy-related costs could potentially be reduced through optical diagnosis strategies, such as 'diagnose-and-leave' a...

Multi-omics integrative analysis of stemness-associated pathological signatures to guide prognosis and therapeutic strategies in uveal melanoma.

BACKGROUND: Uveal melanoma (UVM) is the most common intraocular malignancy in adults and exhibits poor prognosis upon metastasis. Stemness, a hallmark...