Laser Surgery

Optimization of a Radiofrequency Ablation FEM Application Using Parallel Sparse Solvers

Finite element method applications are a common approach to simulate a handful of phenomena but can take a lot of computing power, causing elevated waiting time to produce precise results. The radiofrequency ablation finite element method is an application to simulate the medical procedure of radiofrequency ablation, a minimally invasive liver cancer treatment. The application runs sequentially ...

Identification of A0 minimum ablative margins for colorectal liver metastases: multicentre, retrospective study using deformable CT registration and artificial intelligence-based autosegmentation.

BACKGROUND: Several ablation confirmation software methods for minimum ablative margin assessment have recently been developed to improve local outcomes for patients undergoing thermal ablation of colorectal liver metastases. Previous assessments were limited to single institutions mostly at the place of development. The aim of this study was to validate the previously identified 5 mm minimum abla...

Evaluating the Predictive Features of Person-Centric Knowledge Graph Embeddings: Unfolding Ablation Studies.

Developing novel predictive models with complex biomedical information is challenging due to various idiosyncrasies related to heterogeneity, standard...

Comparative Analysis of Macular and Optic Disc Perfusion Pre and Post Silicone Oil Removal: A Machine Learning Approach.

In the realm of ophthalmic surgeries, silicone oil is often utilized as a tamponade agent for repairing retinal detachments, but it necessitates subse...

VisionUnite: A Vision-Language Foundation Model for Ophthalmology Enhanced with Clinical Knowledge

The need for improved diagnostic methods in ophthalmology is acute, especially in the less developed regions with limited access to specialists and ...

Transformer Circuit Faithfulness Metrics are not Robust

Mechanistic interpretability work attempts to reverse engineer the learned algorithms present inside neural networks. One focus of this work has bee...

[The innovation and challenge of artificial intelligence in the whole process management of fundus disease].

Artificial intelligence (AI) has demonstrated revolutionary potential and wide-ranging applications in the comprehensive management of fundus diseases...

CBCRnet: A Contrastive Learning-based Multi-modal Image Registration Via Bidirectional Cross-modal Attention.

In the past few years, convolutional neural networks (CNNs) have been a major focus in medical image registration. However, it has been proved that CN...

EDRAM-Net: Encoder-Decoder with Residual Attention Module Network for Low-dose Computed Tomography Reconstruction.

The medical application of Computed Tomography (CT) is to provide detailed anatomical structures of patients without the need for invasive procedures ...

Automated Abnormality Detection in Patient Retinal Function: A Deep Learning-Powered Electroretinogram Analysis System.

The electroretinogram (ERG) is an ophthalmic electrophysiology test designed to objectively measure the electrical response of the photoreceptor cells...

Bedside Admittance Control of a Dual-Segment Soft Robot for Catheter-Based Interventions.

Robotic catheters enable precise steering of their distal tip while inside the body's blood vessels, and with this ability comes the need for control ...

[Challenges and prospects in the application of artificial intelligence for ocular disease screening and diagnosis].

In recent years, artificial intelligence (AI) technologies have experienced substantial growth across various sectors, with significant strides made p...

Deep-Learning Approach for Tissue Classification using Acoustic Waves during Ablation with an Er:YAG Laser (Updated)

Today's mechanical tools for bone cutting (osteotomy) cause mechanical trauma that prolongs the healing process. Medical device manufacturers aim to...

THE ABILITY OF ARTIFICIAL INTELLIGENCE CHATBOTS ChatGPT AND GOOGLE BARD TO ACCURATELY CONVEY PREOPERATIVE INFORMATION FOR PATIENTS UNDERGOING OPHTHALMIC SURGERIES.

INTRODUCTION: To determine whether the two popular artificial intelligence chatbots, ChatGPT and Bard, can provide high-quality information concerning...

Validation of a machine learning algorithm to identify pulmonary vein isolation during ablation procedures for the treatment of atrial fibrillation: results of the PVISION study.

AIMS: Pulmonary vein isolation (PVI) is the cornerstone of ablation for atrial fibrillation. Confirmation of PVI can be challenging due to the presenc...

Applications of artificial intelligence in urologic oncology.

PURPOSE: With the recent rising interest in artificial intelligence (AI) in medicine, many studies have explored the potential and usefulness of AI in...

Evaluating the Performance of Large Language Models for Named Entity Recognition in Ophthalmology Clinical Free-Text Notes.

This study compared large language models (LLMs) and Bidirectional Encoder Representations from Transformers (BERT) models in identifying medication n...

An Artificial Intelligence Driven Approach for Classification of Ophthalmic Images using Convolutional Neural Network: An Experimental Study.

BACKGROUND: Early disease detection is emphasized within ophthalmology now more than ever, and as a result, clinicians and innovators turn to deep lea...

Reducing Ophthalmic Health Disparities Through Transfer Learning: A Novel Application to Overcome Data Inequality.

PURPOSE: Race disparities in the healthcare system and the resulting inequality in clinical data among different races hinder the ability to generate ...

Skin Changes in Suspected Lyme Disease.

Dear Editor, Ticks carry many diseases, bacteria, and viruses and represent a very important healthcare issue both in Croatia and globally. Although m...