Ophthalmology

Exploring Older Adults' Use of AI Voice Assistants Through the Lens of Self-Determination Theory.

Aging often reduces opportunities for everyday interaction and instrumental support, raising questions about the potential role of artificial intelligence (AI) technologies in later-life well-being. This study examined how AI voice assistants may fulfill, or fall short of, older adults' basic psychological needs through the lens of self-determination theory (SDT). Eighteen U.S.-based community-dwe...

Automated deep learning-based retinoschisis and detachment volume measurement in pathological myopia with posterior scleral contraction.

PURPOSE: This study developed an automated deep learning-based system to quantify retinoschisis and detachment volume (RDV) in pathological myopia (PM) patients undergoing posterior scleral contraction (PSC). METHODS: A prospective study included 51 PM patients (36 PSC-treated and 15 controls). Based on the myopic traction maculopathy staging system classification, PSC-treated patients were divide...

Clinical artificial intelligence (AI) in Japan: Regulatory pathways, domain-specific evidence, and its data infrastructure from an international perspective.

Artificial intelligence (AI) has advanced rapidly across clinical domains, generating both a growing evidence base and dedicated regulatory frameworks...

Invisible poison attacks and holistic defence strategy for pyramid vision transformers in medical imaging.

Machine learning models, especially vision transformers in the domain of medical images, are highly prone to data poisoning attacks, in which a small ...

The role of artificial intelligence in academic citation: A study on lens, cataract, and anterior segment research.

PURPOSE: To evaluate the accuracy and reliability of four artificial intelligence (AI) models-ChatGPT, Copilot, DeepSeek, and Gemini-in generating Pub...

Deep learning approach for analyzing regional scheimpflug corneal images to assess keratoconus progression.

PURPOSE: To use deep learning models on baseline Scheimpflug corneal images from three different corneal regions to discriminate progressive from nonp...

Where Your Eyes Go: How AI Output Design Impacts Reading Behavior.

The purpose was to examine how variations in AI output design affect radiologists' performance in interpreting chest X-rays. Eight readers interpreted...

Digital Conversation Companions.

Advances in voice recognition and artificial intelligence (AI) could soon yield digital conversation companions-software that combines conversational ...

Real-world integration of an autonomous artificial intelligence system for diabetic retinopathy screening in an endocrinology outpatient clinic.

AIM: To evaluate a real-world clinical integration of an autonomous artificial intelligence (AI) system (AEYE Diagnostic Screening (AEYE-DS), AEYE Hea...

Bacterial keratitis: a global review of current practices, challenges and innovations.

Bacterial keratitis is a major cause of corneal blindness worldwide, with marked differences in clinical presentation and risk factors across regions....

Diagnostic Accuracy of Artificial Intelligence-based Automated Detection of Diabetic Retinopathy in Routine Care Using Nonmydriatic Fundus Images: The Silesia Diabetes-Heart Project.

PURPOSE: To evaluate the diagnostic performance of a regulatory-approved (CE-marked) artificial intelligence system (RetCAD) applied to nonmydriatic c...

Comparative analysis of quantitative fundus results of the left and right eyes and screening for coronary atherosclerotic disease: a binocular study.

BACKGROUND: Retinal microvascular parameters are potential biomarkers for systemic vascular health. This study aimed to assess the interocular consist...

Development of a deep learning model to predict cycloplegic myopia and pre- myopia: based on a large-scale screening of school-aged children.

PURPOSE: This study aims to develop and validate practical deep learning (DL) and machine learning (ML) models to predict cycloplegic myopia, pre-myop...

Gaze-Tracking-Based Tests for Autism in Children: A Diagnostic Test Accuracy Systematic Review and Meta-Analysis.

Atypical gaze patterns are consistently reported in autism, reflecting differences in social attention and interest. Gaze-tracking paradigms provide a...

A multi-scale feature fusion network for CNV segmentation in SD-OCT images toward quantitative assessment of neovascular AMD.

Choroidal neovascularization (CNV) is a characteristic feature of neovascular age-related macular degeneration (AMD), a leading cause of irreversible ...

Cross-attention-based multimodal fusion for early diabetic retinopathy detection.

Early detection of diabetic retinopathy (DR) is crucial for preventing irreversible vision loss; however, existing automated methods often rely on sin...

Deep learning in glaucoma referral: Performance assessment using a real-world setting.

PURPOSE: Evaluate a deep learning model's performance as a pre-referral filter for referable glaucoma using colour fundus photographs. METHODS: Retros...

ORBIT-AMD: Ordinal Risk, Bilateral Imaging, and Trajectory Learning for Age-Related Macular Degeneration in Multi-Cohorts.

Age-related macular degeneration (AMD) is an ordered, bilateral, and longitudinal disease, yet many artificial intelligence systems treat it as static...

Automated iridocorneal angle classification using a multimodal large language model.

PURPOSE: To evaluate the diagnostic performance of a general-purpose vision-language model (GPT-4o) in interpreting gonioscopic images of the anterior...

Estimation of cycloplegic spherical refraction from non-cycloplegic clinical and biometric data in children using machine learning: a retrospective pilot study for screening triage.

OBJECTIVE: To develop and evaluate non-cycloplegic clinical and biometric models for estimating cycloplegic spherical power (DS), spherical equivalent...