Latest AI and machine learning research in laser surgery for healthcare professionals.
BACKGROUND: Timely access to human expertise for affordable and efficient triage of ophthalmic conditions is inconsistent. With recent advancements in publicly available artificial intelligence (AI) chatbots, the lay public may turn to these tools for triage of ophthalmic complaints. Validation studies are necessary to evaluate the performance of AI chatbots as triage tools and inform the public r...
BACKGROUND: In this article, we present a computerized system for the analysis and assessment of diabetic retinopathy (DR) based on retinal fundus photographs. DR is a chronic ophthalmic disease and a major reason for blindness in people with diabetes. Consistent examination and prompt diagnosis are the vital approaches to control DR.
CT metal artefact reduction (MAR) methods based on supervised deep learning are often troubled by domain gap between simulated training dataset and re...
Catheter ablation (CA) is considered as one of the most effective methods technique for eradicating persistent and abnormal cardiac arrhythmias. Never...
Knowledge of critical properties, such as critical temperature, pressure, density, as well as acentric factor, is essential to calculate thermo-physic...
PURPOSE: To compare the oncological and perioperative outcomes of robot-assisted partial nephrectomy (RPN) and percutaneous thermal ablation (PTA) for...
OBJECTIVE: To conduct the first study examining the accuracy of ChatGPT, an artificial intelligence (AI) chatbot, derived patient counseling responses...
PURPOSE OF REVIEW: The current article provides an overview of the present approaches to algorithm validation, which are variable and largely self-det...
OBJECTIVE: To evaluate transperineal laser ablation (TPLA) with Echolaser® (Echolaser® TPLA, Elesta S.p.A., Calenzano, Italy) as a treatment for benig...
Deep neural networks (DNNs) have been widely applied in the medical image community, contributing to automatic ophthalmic screening systems for some c...
Low-dose computed tomography (LDCT) is an effective way to reduce radiation exposure for patients. However, it will increase the noise of reconstructe...
Our approach addresses the urgent need for AI experience for the doctors of tomorrow. Through a medical education-focused approach to data labelling, ...
INTRODUCTION: Highly complex renal masses pose a challenge to urologic surgeons' ability to perform robotic partial nephrectomy (RPN). Given the incre...
Diabetic retinopathy is a leading cause of blindness in working-age adults worldwide. Neovascular leakage on fluorescein angiography indicates progres...
In medicine, confounding variables in a generalized linear model are often adjusted; however, these variables have not yet been exploited in a non-lin...
PURPOSE: To compare the inter-camera performance and consistency of various deep learning (DL) diagnostic algorithms applied to fundus images taken fr...
OBJECTIVE: Robot-assisted (RA) stereotactic MRI-guided laser ablation has been reported to be a safe and effective technique for the treatment of epil...
The da Vinci single-port (SP) platform represents the latest innovation in minimally invasive urologic surgery, and the adoption of this technology b...
OBJECTIVE: The goal of the work described here was to construct a deep learning-based intelligent diagnostic model for ophthalmic ultrasound images to...