Laser Surgery

A deep learning model integrating structured data and clinical text for predicting atrial fibrillation recurrence.

Multimodal perioperative data from patients undergoing atrial fibrillation (AF) ablation offer valuable insights for stratifying recurrence risk, yet remain underutilized in prediction models. This multicenter retrospective study included 2508 patients who underwent AF ablation at five Chinese centers: The Fourth Affiliated Hospital of Zhejiang University School of Medicine (Jan 2016-Mar 2024; Tra...

Research on the Prediction of Coal Workers' Pneumoconiosis Based on Easily Detectable Clinical Data: Machine Learning Model Development and Validation Study.

BACKGROUND: Coal workers' pneumoconiosis (CWP) is the most prevalent occupational disease that causes irreversible lung damage. Early prediction of CWP is the key to blocking the irreversible process of pulmonary fibrosis. The prediction of CWP based on imaging data and biomarker detection is constrained due to high cost and poor convenience. OBJECTIVE: The study aimed to use easily detectable cli...

An update on the developments and challenges with the diagnosis and classification of autoimmune optic neuritis.

INTRODUCTION: Autoimmune optic neuritis (ON) is a heterogeneous spectrum that includes multiple sclerosis (MS), neuromyelitis optica spectrum disorder...

From Observation to Prediction: Machine Learning Analysis of Progression of Visual loss in Nonarteritic Anterior Ischemic Optic Neuropathy.

OBJECTIVE: To determine whether combinations of modifiable clinical/systemic risk factors and structured trial variables predict early disease progres...

Can atrial fibrillation ablation outcomes be properly predicted with electrocardiography and artificial intelligence?

AIMS: The success of ablation for atrial fibrillation (AF) varies, often leading to repeat ablation. Reliable prediction of repeat ablation remains ch...

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 a...

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...