Ophthalmology

A hybrid model for early diagnosis of ophthalmology diseases leveraging CNNs, SBOA optimization, and XAI for visualization.

Ophthalmology diseases are among the leading causes of vision loss worldwide. Glaucoma, diabetic ret...

Construction and Applications of Knowledge Graphs in Ophthalmology.

Knowledge Graph (KG) is an artificial intelligence technique that provides a structured representati...

Artificial intelligence-assisted detection and optical differentiation of colorectal lesions in Lynch syndrome surveillance (CADLY2): a multicentre, open-label, randomised controlled superiority trial.

BACKGROUND: Artificial intelligence (AI)-based computer-aided detection (CADe) systems improve adeno...

Machine learning-based model for identifying liver injury in patients with thyroid-associated ophthalmopathy.

PURPOSE: To explore the relationship between thyroid-associated ophthalmopathy (TAO) and liver injur...

A hybrid vision-language artistic images aesthetic evaluation framework based on cross-modal attention and differential evolution.

Aesthetic evaluation of artistic images remains a challenging prediction problem, constrained by the...

Comment on: Enhancing patient education in cataract surgery using a conversational artificial intelligence chatbot: pilot randomized controlled trial.

Reply: Enhancing Patient Education in Cataract Surgery Using a Conversational Artificial Intelligence Chatbot: A Pilot Randomized Controlled Trial.

A modern review of uveal melanoma: molecular insights, clinical management, and emerging therapies.

Uveal melanoma is the most frequent primary intraocular malignancy in adults and is characterized by...

Real-world clinical validation of brainstem-based ocular biomarkers for ADHD classification in children and adults.

Current ADHD diagnostic practices rely on subjective rating scales and continuous performance tests ...

ERDES: A Benchmark Video Dataset for Retinal Detachment and Macular Status Classification in Ocular Ultrasound.

Retinal detachment (RD) is a vision-threatening condition that requires prompt intervention to prese...

Tree-based machine learning models recover rule-based flare labels from virtual symptom diaries in pediatric Behçet's disease: an in silico proof-of-concept study.

Behçet's disease (BD) in childhood is characterised by recurrent inflammatory flares that can result...

Prism-refraction K-means polar lights optimizer-driven feature selection for accurate diabetes diagnosis.

This study developed a machine learning framework for stratifying abnormal glucose tolerance risk am...

Neurobiosensory and Visual Patterns of Attentional and Emotional Functioning in Children: A Machine Learning Approach.

BACKGROUND: Attentional functioning in childhood emerges from the interaction between cognitive, beh...

Predicting Neonatal Respiratory Outcomes Using Machine Learning: A Systematic Review Through a Life Course Lens.

BACKGROUND: Neonatal respiratory outcomes remain leading drivers of neonatal intensive care unit (NI...

High-performance surface plasmon resonance biosensor design: Encircled quad-block resonator structure for real-time label-free detection of marijuana assisted with linear regression.

In the last few years, chemical analysis and chromatography approaches have been implemented widely ...

Fractal Sierpinski triangle block division for retina-based glaucoma detection using an optimized hybrid deep learning model.

Glaucoma is a primary cause of permanent vision loss, and it often gets worse without anybody notici...

A classification model for predicting corticosteroid and cyclosporin: A responsiveness in pediatric idiopathic uveitis.

BACKGROUND: To identify serum metabolic biomarkers that distinguish corticosteroid and cyclosporin A...

Machine learning model for the detection of autism spectrum disorder using electroretinogram signals.

Autism Spectrum Disorder (ASD) is a neurodevelopmental disease marked by limited or repetitive behav...

[Artificial intelligence in neuro-ophthalmology: prospects, challenges and countermeasures].

Neuro-ophthalmic disorders feature complex etiology. Certain ocular manifestations may hint at sever...

Non-advanced age-related macular degeneration: current concepts and future perspectives.

Non-advanced age-related macular degeneration (AMD), encompassing early and intermediate stages, rep...

An exploratory SMOTE-SVM approach for identifying preoperative biomechanical risk factors driving early toric intraocular lens micro-rotation in extremely imbalanced cohorts.

The predictive modeling of postoperative mechanical complications, such as the early micro-rotation ...