Ophthalmology

Evaluation of a Collaborative Telehealth Model for Eye Care Between Ophthalmology and Optometry in Western Australia.

OBJECTIVE: Recent advances in technology and the impact of COVID-19 have expanded the adoption of digital health. Synchronous collaborative telehealth between optometry and ophthalmology has been used to expedite specialist eye care in Western Australia since 2011. Optometrists perform an in-person assessment and participate in videoconferencing with ophthalmology to facilitate shared decision-mak...

Literature Commentary June, 2026.

In this issue, the following 4 articles are reviewed by Drs. Mark L. Moster and Deborah I. Friedman, most of which include authors who are members of NANOS:Pakeerathan T, Davis J, Henderson AD, et al. OCT-based differentiation of first acute optic neuritis: an international study of 111 patients with NMOSD and MOGAD. Neurol Neuroimmunol Neuroinflamm. 2026;13:e200531. Brownlee WJ, Maccarrone D, Nis...

Large Language Models for Ophthalmology Training in China: A Prospective Evaluation.

PURPOSE: This study explored large language models (LLMs) as a scalable solution to the global shortage and uneven distribution of ophthalmologists, p...

LLM-guided expert feature extraction with fusion-based complementary learning network for fish freshness classification using eye images.

Accurate, non-invasive grading of fish freshness remains challenging in dense and occluded environments, where the fish eye images serve as a reliable...

[Artificial intelligence in diabetic retinopathy screening].

INTRODUCTION: Visual impairment and blindness continue to represent a substantial disease burden in Hungary. According to national epidemiological dat...

Field-based and close-range multispectral imaging dataset for Huanglongbing (HLB) detection in orange trees: A resource for machine learning and digital agriculture.

This article presents a multispectral imaging dataset dedicated to training a machine learning algorithm for the in situ detection of Huanglongbing (H...

Does lens opacity matter? The effect of cataract on deep learning based cardiovascular disease risk scores from fundus photos.

PURPOSE: To investigate the effect of cataracts on a deep learning (DL) model for cardiovascular disease (CVD) risk prediction. METHODS: This retrospe...

Artificial intelligence can replace nursing tasks, but not nurses: Examining artificial intelligence's supports and threats to nursing practice through the lens of the 2025 Nursing Code of Ethics.

BACKGROUND: Nurses are concerned that artificial intelligence (AI) could undermine the holistic, intuitive, and experience-based clinical judgment tha...

Application of construction and validation of logistic regression model in risk prediction of non-proliferative diabetic retinopathy in type 2 diabetes mellitus.

AIMS: Diabetic retinopathy (DR) is a leading cause of vision impairment in type 2 diabetes mellitus (T2DM), with non-proliferative DR (NPDR) represent...

Advances in Clinical Imaging and AI Integration for Dry Eye Diagnosis.

Dry eye disease (DED) is a prevalent multifactorial chronic disorder of the ocular surface, characterized by a loss of tear film homeostasis and accom...

Artificial intelligence in cardiovascular care for internal medicine: from promising algorithms to useful clinical services.

Artificial intelligence is expanding rapidly in cardiovascular medicine, but its value in internal medicine depends less on raw model performance than...

Deep Learning-Based Quantification of Vitreous Hyperreflective Foci as a Biomarker for Intraocular Inflammation.

OBJECTIVE: To develop and validate an artificial intelligence (AI)-driven pipeline to quantify vitreous hyperreflective foci (vHRF) from OCT images an...

Integrated multi-endpoint hazard prioritization of unregulated industrial contaminants: A safety-first screening framework for emerging environmental threats.

The rapid expansion of the industrial chemical space has outpaced regulatory oversight, creating a critical regulatory and environmental blind spot re...

Deep learning for early detection of guava fruit anthracnose and fruit fly infestation.

Anthracnose and fruit fly infestation are major biotic constraints on guava (Psidium guajava) production in South Asia, causing substantial yield loss...

Displaced minds: ecologies of depression.

This issue of the Biomedical Journal explores emerging perspectives across neuropsychiatry, metabolism, aging, regenerative medicine, artificial intel...

Precision Management of Autoimmune Ocular Complications: Th17 Mechanisms and Therapeutic Innovations.

Precision management of ocular complications in systemic autoimmune diseases, such as Sjögren's syndrome (SS), systemic lupus erythematosus (SLE), Beh...

AI-Driven Oculomics-The Brain-Retina Connection.

AI driven Hybrid CNN transformer model for early detection and severity assessment of diabetic retinopathy.

As the major cause of sight impairment in working age adults is diabetic retinopathy (DR) which requires timely and proper diagnosis to avoid the irre...

Combined diagnostic accuracy of two artificial intelligence systems for glaucoma diagnosis using color fundus photography.

PURPOSE: To evaluate the diagnostic accuracy of two commercially available artificial intelligence (AI) systems based on color fundus photography (CFP...

Rapid Access Macular Screening and Evaluation: A Datasheet for a Dataset to Diagnose and Triage Macular Diseases.

PURPOSE: Macular disease can cause significant visual morbidity. Timely and accurate diagnosis and management is paramount. However, there is a lack o...