Ophthalmology

Medical AI Agents for Clinical Decision Support: Viewpoint Using the Planning, Action, Reflection, and Memory (PARM) Analytical Lens.

Medical AI agents are emerging as a new generation of clinical decision support systems, moving beyond static prediction toward multistep, workflow-oriented assistance. This Viewpoint argues that agentic architectures incorporating planning, action, reflection, and memory (PARM) represent a meaningful evolution beyond traditional rule-based, machine learning, and multimodal clinical decision suppo...

The Algorithm's Blindspot: An Ethical Critique of Data-Fetishism and the Deskilling of the Clinical Gaze in Ophthalmology.

The rapid integration of artificial intelligence (AI) in ophthalmology has produced remarkable diagnostic accuracy while simultaneously raising significant ethical and epistemic concerns. This article argues that the prevailing AI paradigm fosters a form of data-fetishism: the tendency to treat datasets and algorithmic outputs as objective truth, privileging measurable metrics over the patient's l...

GENERALIZABILITY OF DEEP LEARNING MODELS FOR REFERABLE DIABETIC RETINOPATHY DETECTION: A CROSS-POPULATION STUDY.

PURPOSE: To evaluate cross-population performance of deep learning models for referable diabetic retinopathy (DR) detection and assess whether inclusi...

An Attention-Based Transformer Algorithm Integrated with YOLO Framework for Lesion Localization and Detection Diabetic Retinopathy.

Diabetic Retinopathy (DR) is one of the major causes of vision loss among diabetic patients across the globe, and it is a major challenge to the publi...

Reticular pseudodrusen load is associated with an increased risk of stroke.

BACKGROUND/AIMS: Reticular pseudodrusen (RPD) are increasingly recognised as a distinct phenotype in the age-related macular degeneration (AMD) diseas...

Regional differences in foveal avascular zone morphology in cynomolgus macaques using a normative OCTA database.

Cynomolgus macaques are widely used in preclinical ophthalmic research because of their close anatomical and physiological similarity to the human eye...

Exploratory development of prediction models for pharmacotherapy outcomes in trigeminal neuralgia: a combined analysis based on multi-source data.

BACKGROUND: Drug-refractory trigeminal neuralgia (DRTN) represents a formidable challenge in clinical management, with approximately 30%-50% of patien...

Decoding dry eye disease based on bioinformatics and in vitro experimental: the role of immune responses and natural product intervention.

BACKGROUND: Dry eye disease (DED), a prevalent ocular condition, has seen rising incidence rates. Aberrant inflammation and immune dysregulation are k...

Oculomics: advances and perspectives from traditional Chinese medicine to modern multimodal biomarkers.

Oculomics, the study of the relationship between ophthalmic biomarkers (changes or abnormalities in the eye) and systemic health or disease states, po...

Artificial intelligence for diagnosis of keratoconus using Scheimpflug based corneal tomography.

AIM: To develop and evaluate the diagnostic accuracy of deep learning (DL) models in differentiating keratoconus (KC) from normal eyes with regular as...

Recent developments in the therapeutic management of acid-related gastrointestinal diseases.

INTRODUCTION: Acid-related gastrointestinal diseases, particularly gastroesophageal reflux disease (GERD) and peptic ulcer disease (PUD), remain major...

Live-Cell Imaging Enables Reporter-Free Monitoring Of The Circadian Rhythm In Individual Synechocystis Cells.

In vivo monitoring of circadian rhythms depends on reliable and non-invasive detection methods. This is often achieved by expressing reporter genes he...

Reconfigurable ferroelectric transistor array for embodied neuromorphic vision with hardware-native sensing, computing, and activation.

Edge artificial intelligence (AI) and embodied vision call for compact, fast, and energy-efficient hardware that integrates sensing, linear analog com...

Preliminary Analysis of Biomarkers and Molecular Mechanisms in Graves' ophthalmopathy Patients Related to the Retinol Metabolic Pathway.

OBJECTIVE: This study aimed to identify potential biomarkers for Graves' ophthalmopathy (GO) through bioinformatics analyses and to validate their exp...

A CT-based deep learning model for the automated risk stratification of refractory Mycoplasma pneumoniae pneumonia in children.

BACKGROUND: The accurate identification of children with refractory Mycoplasma pneumoniae pneumonia (RMPP) remains challenging. This study aimed to de...

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 retinopathy, and cataracts are the most common diseas...

Construction and Applications of Knowledge Graphs in Ophthalmology.

Knowledge Graph (KG) is an artificial intelligence technique that provides a structured representation of medical entities and their relationships, th...

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 adenoma detection in average-risk colorectal cancer scr...

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 injury and establish a model for identifying liver inju...

Temporal shifts and relationships of emotions in social and mass media: A case study of the "Reiwa Rice Riot" in Japan.

In Japan, severe rice shortages in 2024 sparked widespread public controversy across both news media and social platforms, culminating in what has bee...