Laser Surgery

Artificial Intelligence Enabled Noninvasive Mapping of Cardiac Arrhythmia Origins Using the 12-Lead Electrocardiogram.

Artificial intelligence (AI) is reshaping cardiac electrophysiology by extracting information from electrocardiograms that exceeds human visual interpretation. While most AI applications have focused on arrhythmia detection and risk stratification, a newer and more targeted use case is emerging: noninvasive localisation of arrhythmia origins from a standard 12-lead electrocardiogram (ECG). This re...

Study of bladder cancer detection in standard white light versus AI-supported endoscopy-01 (RAISE-01) - Development and validation of an AI-based support tool.

BACKGROUND: Diagnosis and surveillance of bladder cancer rely on white-light cystoscopy (WLC). However, this modality is operator-dependent and associated with a risk of missed lesions, contributing to high recurrence rates, especially in non-muscle invasive bladder cancer. Recent advances in artificial intelligence (AI) enable software-based decision support for bladder lesion detection, with pot...

Routine blood tests and machine learning identify complications in high myopia.

High myopia can lead to cataract, glaucoma, retinal detachment, choroidal neovascularisation, and macular degeneration, causing irreversible vision lo...

Integrating traditional statistics and explainable machine learning for risk stratification of atrial fibrillation recurrence after pulsed field ablation: a hypothesis-generating single-center study.

BACKGROUND: Predicting recurrence after pulsed field ablation (PFA) for paroxysmal atrial fibrillation (AF) remains challenging, particularly in early...

Why nonlinear models matter: unified analysis of cognitive load, stress, and exercise using wearable physiological signals.

\textbf{Objective:} Physiological measurements obtained from wearable devices reflect complex autonomic nervous system dynamics that are often ass...

Real world practice of Artificial intelligence Diagnostic System for Diabetic Retinopathy in Taiwan.

PURPOSE: We evaluated the alterations of applying artificial intelligence (AI) diagnostic system for diabetic retinopathy (DR) screening in real-world...

Multimodal MRI radiomics for predicting HIFU ablation efficacy in uterine fibroids: a machine learning study.

OBJECTIVE: To explore the predictive value of machine learning-based multimodal MRI radiomics combined with clinical features in the efficacy of high-...

Toward Long-Term Visual Field Appearance Forecasting Using Artificial Intelligence for Ophthalmic Education and Diagnosis.

OBJECTIVE: To provide state-of-the-art, post hoc-explainable visual field (VF) forecasts to aid in training ophthalmic residents to characterize glauc...

Simulated Patient Queries Reveal Limitations of ChatGPT in Dermatologic Image Classification.

[Application of artificial intelligence in pathological diagnosis of ocular tumors].

Ocular tumors encompass ocular surface tumors, orbital tumors, and intraocular tumors, characterized by high heterogeneity and complex classifications...

Latent Supervision: A Method for Improved Performance and Calibration of Machine Learning Classification Models in Ophthalmology.

PURPOSE: Standard supervised learning assumes deterministic labels (e.g., positive or negative, present or absent), neglecting the diagnostic uncertai...

Bridging Population Patterns and Individual Prediction: Framework for Prospective Multimorbidity Study.

BACKGROUND: Multimorbidity has become a major global public health challenge. However, existing research primarily emphasizes the identification of di...

Synthetic skin image generation using a physics-based, object-to-image computational pipeline.

PURPOSE: We describe an extended overview and evaluation of the S-SYNTH skin simulation approach (Kim et al. in MICCAI, Springer, pp 734-744, 2024), a...

Human-in-the-loop validation of an artificial intelligence-driven real-time prostatic capsule recognition model for nerve-sparing robot-assisted radical prostatectomy.

BACKGROUND: Nerve-sparing robot-assisted radical prostatectomy (NS-RARP) requires precise prostatic capsule identification to balance oncological cont...

Funders' Role in Ophthalmic Artificial Intelligence Innovations.

An ophthalmic video foundation model for surgical recognition and navigation with wet-lab porcine eye validation.

Foundation models in artificial intelligence are revolutionizing healthcare by utilizing large-scale unlabelled data for pretraining. However, their i...

A test-time clinically adaptive framework for detecting multiple fundus diseases harnessing ophthalmic foundation models.

Fundus diseases are leading causes of global vision impairment, often presenting with complex comorbidities that challenge conventional artificial int...

Updates in Central Retinal Artery Occlusion.

BACKGROUND: Central retinal artery occlusion (CRAO) is a vision-threatening neuro-ophthalmic emergency, analogous to acute ischemic stroke. Delayed pr...

An interpretable molecular descriptor for machine learning predictions in atmospheric science.

The study of aerosol formation and chemistry using machine learning is limited by the lack of molecular descriptors suited to atmospheric compounds. I...

Domain-Shift AI Technology for Vendor-Agnostic Multiple Macular Disease Detection From 3D OCT Scans.

IMPORTANCE: A deep learning (DL) model capable of analyzing optical coherence tomography (OCT) 3-dimensional (3D) scans from various vendors is essent...