Laser Surgery

TriFTM-Net: Tri-Path Fourier-Temporal Modulation Network for macular edema pathology segmentation and reconstruction in high-precision intraoperative navigation.

Ophthalmic diseases such significantly impair the vision of numerous individuals globally. Accurate and real-time 3D reconstruction of macular edema and retinal tears is crucial for improving surgical efficiency and success rates. However, lesion areas often exhibit considerable noise and high heterogeneity, and the imaging devices employed may introduce electronic noise and artifacts. Current 2D ...

Accuracy of Artificial Intelligence-Assisted CPT Coding in Dermatologic Surgery.

Dual Framework for Classification and Detection of Third Molar Impaction in Panoramic Radiographs.

BACKGROUND: The surgical extraction of impacted mandibular third molars present significant clinical challenges, where accurate preoperative assessmen...

Agentic artificial intelligence in ophthalmology: Toward autonomous, adaptive, and ethical eye care.

Agentic artificial intelligence (AI) represents a new generation of intelligent systems capable of autonomous goal-directed reasoning, dynamic decisio...

Real-world performance of an AI system for diabetic retinopathy screening.

Diabetic retinopathy (DR) is a leading cause of preventable blindness, and the growing global burden of diabetes is placing increasing pressure on oph...

AI-enhanced robotic hands: a breakthrough in early tumour detection and removal.

AI-enhanced robotic hands are rapidly reshaping tumour surgery by merging real-time sensing, precision mechanics, and intelligent decision support, ye...

Experimental and ANN-based analysis of performance, combustion, and emission characteristics of a CI engine fueled with waste plastic oil-diethyl ether-diesel blends.

This study differs fundamentally from prior investigations on WPO-diesel and WPO-DEE blends by combining combustion-resolved experimentation with pred...

Ultrasound-guided microwave ablation for breast tumors: current status and future perspectives.

Ultrasound (US)-guided microwave ablation (MWA) has emerged as a promising minimally invasive therapy for both benign and malignant breast tumors. Thi...

Shaping the future of myopia: artificial intelligence for vitreoretinal complications of high and pathologic myopia.

PURPOSE: The global impact of myopia extends far beyond individual ocular health, posing significant challenges to healthcare systems worldwide. Artif...

Robust Distance Estimation with Out-of-distribution Detection in Ophthalmic Surgery.

OBJECTIVE: Micrometer-scale precision is vital for patient safety in ophthalmic surgery. Recent advancements in instrument-integrated optical sensors ...

Reablation of atrial fibrillation targeting electrogram dispersion in patients with isolated veins: The RESTART trial.

BACKGROUND: Pulmonary vein (PV) isolation is a well-established treatment for atrial fibrillation (AF), however, strategies for patients with recurren...

A machine learning gap-filling approach for daily forest soil CO2 flux based on environmental factors and eddy covariance variables.

Accurate gap-filling of daily soil CO₂ flux is essential for understanding forest carbon cycling and supporting the achievement of carbon neutrality g...

Data-related Ablation for Reinforcing Deep Learning in Explaining Complex Phenomena.

Deep Learning (DL) models excel at automatically learning intricate patterns within complex data, but their black box nature undermines human trust. T...

Foundation models for ophthalmic imaging.

Foundation models represent a new frontier in ophthalmic artificial intelligence, enabling learning of transferable features from large unlabelled ima...

Roof-dependent atrial tachycardia after pulsed field ablation-mechanistic insights and predictive modeling for optimized ablation strategies: an ultra-high-density mapping study.

BACKGROUND AND AIMS: Pulsed field ablation (PFA) has emerged to an innovative approach to achieve pulmonary vein isolation (PVI) in atrial fibrillatio...

A hybrid CNN and reinforcement learning framework for speaker identification using Mel-Spectrogram and continuous wavelet transform features.

Speaker identification remains critical in biometric authentication systems, requiring robust feature extraction strategies that capture speaker-speci...

6G conditioned spatiotemporal graph neural networks for real time traffic flow prediction.

Accurate, low-latency traffic forecasting is a cornerstone capability for next-generation Intelligent Transportation Systems (ITS). This paper investi...

Evolving strategies may facilitate oral pathology and cancer surveillance, monitoring, and detection for patients at risk.

BACKGROUND: Oral cancers account for considerable morbidity and mortality worldwide, and their incidence has increased in the past several years, desp...

Therapeutic nanofibrous scaffolds in precision drug delivery: formulation design, challenges and regulatory frameworks.

INTRODUCTION: Drug-loaded nanofibrous systems represent a breakthrough in drug delivery, overcoming limitations of conventional formulations. They dem...

[Enhancement of radiomics-based machine learning models for predicting efficacy of high-intensity focused ultrasound ablation of uterine fibroids using undersampling methods].

OBJECTIVES: To improve the accuracy of machine learning models for preoperative prediction of high-intensity focused ultrasound (HIFU) ablation effica...