Ophthalmology

Spatial synaptic pruning mechanism of NAC microglia in differential regulation of PTSD- and depression-like behaviors.

BACKGROUND AND AIMS: Post-traumatic stress disorder (PTSD) comorbid with depression is a prevalent, treatment-refractory clinical syndrome. Emerging evidence indicates shared microglial alterations in PTSD and depression, suggesting it may represent a common pathological substrate. However, the underlying neuroimmune mechanisms remain unclear. METHODS: PTSD- and depression-like behaviors were indu...

Evaluation of Large Language Model-Generated Recommendations in Glaucoma Surgical Decision-Making.

OBJECTIVE: To evaluate the utility, rationality, and safety of glaucoma surgery recommendations generated by three prominent large language models (LLMs) - ChatGPT, Microsoft Copilot, and Google Gemini - when applied to real-world clinical scenarios. METHODS: Retrospective records from a tertiary hospital were converted into standardized scenarios and stratified into "primary" and "complex" glauco...

Application of Artificial Intelligence in Diagnosis and Management of Thyroid Disease.

Artificial intelligence (AI) is transforming thyroid care, with applications spanning ultrasound risk stratification, cytopathology, histopathology, r...

Development of a machine-learning risk stratification tool for vasoactive medication need after two-bolus fluid resuscitation in pediatric suspected sepsis.

BACKGROUND: Timely vasopressor initiation is critical in fluid-refractory pediatric septic shock, yet clinicians lack objective tools to identify chil...

Volumetric reference data of the orbit: a deep learning MRI analysis in the German national cohort.

Manual segmentation of orbital magnetic resonance imaging (MRI) is labor-intensive, hindering large-scale morphometric studies. To overcome this, we d...

Navigating regulatory fragmentation in the convergence of synthetic biology, artificial intelligence, and automation.

The convergence of synthetic biology, artificial intelligence (AI), and automation (SynBioxAI) creates research activities that simultaneously engage ...

Early Retinal UCHL1 Dysregulation Coupled With Synaptic Loss Reflects Alzheimer's Disease Severity.

Synaptic dysfunction is a major driver of cognitive decline in Alzheimer's disease (AD), yet its extent and molecular basis in the retina remain poorl...

From clinical and typical separation to autism spectrum disorder and global developmental delay differentiation: Interpretable eye-tracking-based machine learning.

In clinical practice, objectively distinguishing children with autism spectrum disorder (ASD) from those with typical development (TD) and other neuro...

Community-based paediatric eye care in low- and middle-income countries: bridging the gap between policy and practice.

Childhood visual impairment and blindness remain major public health concerns in low- and middle-income countries (LMICs), despite a substantial propo...

Performance and label efficiency of traditional deep-learning models and a retina-specific foundation model for ocular and systemic disease detection: a retrospective comparative study.

BACKGROUND: RETFound, a self-supervised retina-specific foundation model, has shown potential in downstream tasks, but its performance in comparison w...

Workflow evaluation of a commercial deep learning-based image analysis tool for the quantification of angiogenesis in vivo.

Angiogenesis plays a crucial role in tumor development as well as in wound healing and integration of biomaterials. However, quantification of complex...

Brain Tumor Classification from MRI Using Colormap-Based Vision Transformers on the BRISC2025 Dataset.

Accurate brain tumor classification from magnetic resonance imaging (MRI) is essential for supporting early diagnosis and treatment planning. While Vi...

Labeling matters: A multicenter machine learning study on visual field progression in Glaucoma.

BACKGROUND: To compare machine learning (ML) performance for detecting visual field (VF) progression across different labeling strategies using a larg...

Enhanced diabetic retinopathy detection via multimodal fusion of fundus imaging features and clinical demographic information using verifiable convolutional neural network.

Traditional systems of ocular disease diagnosis and many deep learning-based systems are limited in their practice to analyzing fundus images from a s...

A comparative study of vision transformer architectures for the detection of Alzheimer's disease using magnetic resonance images.

Alzheimer's disease is a neurodegenerative disease that affects millions of people worldwide. With the increasing global elderly population, early and...

Machine learning prediction of human blood optical properties: a comparative study of optimized algorithms with SHAP-based interpretability analysis.

Accurate characterization of the optical properties of blood is essential for biomedical optics, diagnostic imaging, and therapeutic applications. con...

Artificial intelligence for healthcare in Nepal: A scoping review of clinical applications, implementation evidence, and health-system governance.

BACKGROUND: Nepal offers a distinctive LMIC setting for evaluating AI-health adoption due to its difficult geography, specialist shortage, high case b...

Glycosylation-Associated Macrophage Signatures Define a Diagnostic Model for Diabetic Retinopathy via Single-Cell Analysis.

PURPOSE: Diabetic retinopathy (DR) remains a leading cause of vision loss, with macrophages and glycosylation dysregulation implicated in DR pathogene...

Deep Learning Versus LASSO-Based Machine Learning for 1-Year Survival After Surgery for Spinal Metastases: A JASA Multicenter Prospective Cohort Analysis.

STUDY DESIGN: Multicenter prospective cohort study; secondary analysis. OBJECTIVE: To evaluate predictors associated with 1-year survival after surger...

The Future of Healthcare Leadership Education: A Consensus Vision and Research Agenda from an International Working Group.

Healthcare systems worldwide face escalating complexity driven by workforce shortages, increasing patient acuity, interprofessional practice demands, ...