Laser Surgery

Image Distortion Correction for Diffusion MR Imaging Using a Transformer-based U-Net.

PURPOSE: To evaluate the performance of a Transformer-based U-Net, TransDisCo, for distortion correction in clinical diffusion-weighted imaging (DWI), including high b-value DWI, diffusion tensor imaging (DTI), and diffusion kurtosis imaging (DKI) and, furthermore, to compare its efficacy with an established U-Net-based method (Synb0) on a clinical dataset including lesion cases. METHODS: This stu...

Political determinants of melanoma: Global inequities in skin cancer care.

BACKGROUND: Melanoma outcomes differ across countries, income settings, and skin tones, reflecting not only variable environmental and genetic risks but also upstream political determinants of health that shape exposure, access, and resources. OBJECTIVE: To apply the 3-I framework (Interests, Ideas, and Institutions) to synthesize global melanoma inequities and identify actionable dermatologic imp...

Transfer learning for Multi-institutional Classification of Intussusception and Splenomegaly in Pediatric Abdominal Radiographs.

To address diagnostic delays in pediatric abdominal emergencies, this study aimed to develop and validate multi-institutional deep learning models for...

Machine learning-based prediction of diabetic retinopathy using clinlabomics: a multi-center study.

BACKGROUND: Diabetic retinopathy (DR) is a leading cause of vision loss, yet conventional retinal screening remains costly and resource-intensive. Thi...

Rethinking scale in ophthalmic artificial intelligence: from bigger models to smarter clinical reasoning.

Recent advances in ophthalmic AI have improved benchmark performance, yet clinical trust remains limited. We argue that progress should move beyond da...

Advanced computer-aided diagnosis for age-related macular degeneration: integrating segmentation and feature extraction for precise diagnosis.

Age-related Macular Degeneration (AMD) is a leading cause of vision loss globally; necessitating early detection and precise diagnosis for effective i...

Predicting atrial fibrillation recurrence after radiofrequency ablation using the AIFV system: a prospective observational study.

BACKGROUND: Pulmonary vein isolation (PVI) has become the cornerstone of atrial fibrillation (AF) treatment. Nevertheless, the efficacy of radiofreque...

Comparative analysis of large language models and clinicians in thyroid eye disease using structured questionnaires.

To preliminarily evaluate agreement between large language models (LLMs) and ophthalmic clinicians regarding thyroid eye disease (TED) clinical decisi...

Automated phenotyping of ophthalmologic diseases from routine medical records using small language models and the human phenotype ontology (HPO).

Automated phenotyping in ophthalmology requires accurate standardization of clinical terms to facilitate interoperability and research. This study eva...

Research on a lightweight model for laser-cut diamond defect detection based on multi-module collaborative optimization.

As a high-end abrasive material, diamond is prone to defects such as cracks and ablation during laser cutting due to complex physical interactions. Ac...

Global approval and certification of ophthalmic AI devices: A comparative regulatory perspective.

Artificial intelligence (AI) tools are rapidly reshaping ophthalmology by improving screening and diagnosis for diabetic retinopathy, age-related macu...

Surgical technology update for ophthalmic surgery: heads-up display, artificial intelligence, instrumentation, and robotics.

PURPOSE OF REVIEW: Rapid advances in surgical visualization, microsurgical instrumentation, artificial intelligence (AI), and robotic assistance are r...

Physics-informed neural networks for predicting laser-tissue interaction in maxillofacial reconstruction surgery.

This study employs Physics-Informed Neural Networks (PINNs) to simulate the thermal dynamics of biological tissue under laser irradiation by embedding...

Smartphone-based lightweight AI system for real-time multiple anterior segment disease screening: development and real-world validation.

BACKGROUND: Anterior segment diseases are a major global cause of preventable blindness, especially in regions with limited access to specialized opht...

Artificial intelligence in retinoblastoma and uveal melanoma: a narrative review.

INTRODUCTION: Artificial intelligence (AI) is reshaping diagnostic paradigms across oncology. In ophthalmic oncology encompassing conditions like reti...

Early volume reduction slope as a novel predictor of long-term outcomes following microwave ablation of benign thyroid nodules: a machine learning-enhanced prediction model.

OBJECTIVE: This study aimed to develop and validate a predictive model incorporating early VRR slope kinetics to predict long-term treatment outcomes....

Focused Ultrasound in Brain Tumors: Mechanisms, Imaging Guidance, and Emerging Clinical Applications.

Focused ultrasound (FUS) is an emerging therapeutic and diagnostic technology in neuro-oncology, offering new strategies for molecular diagnosis, drug...

Classification of retinal diseases based on optical coherence tomography angiography using cross-modal transfer learning of domain-specific foundation AI models.

AIMS: This study evaluated the use of ophthalmic foundation deep-learning models with cross-modal transfer learning to classify multiple diseases on o...

The aging eye: navigating molecular mechanisms and innovative interventions.

The global demographic shift toward aging has precipitated a surge in age-related ocular pathologies, imposing a formidable public health challenge th...

Artificial Intelligence in Urologic Documentation: A Review of Emerging Capabilities and the Ongoing Need for Human Oversight.

PURPOSE OF REVIEW: Clinical documentation continues to expand in volume and complexity, spanning outpatient encounters, inpatient summaries, patient-p...