Laser Surgery

Atrial Fibrillation Recurrence After Catheter Ablation: The Puzzle We Have and the Pieces We Need.

Atrial fibrillation (Afib) recurrence following catheter ablation (CA) remains a significant challenge within the electrophysiology community, potentially driven by complex mechanisms and diverse patient characteristics. Although multiple predictors of recurrence have been investigated, only a limited number have been consistently validated across studies, suggesting uncertainty in their predictiv...

UNIK (Urologic Non-Neoplastic Investigation of Kidneys): a machine learning approach to decode benign lesion.

PURPOSE: Predicting the likelihood of benign neoplasia in patients with suspected renal cell carcinoma (RCC) is a cornerstone of presurgical planning. We sought to create and validate U.N.I.K., a machine learning (ML) model capable of predicting benign lesions on final histological report.

Energy consumption analysis and prediction in exercise training based on accelerometer sensors and deep learning.

This study aims to enhance the accuracy and efficiency of energy consumption prediction during exercise training and address the limitations of existi...

Effectiveness of smartphone technology for detection of paediatric ocular diseases-a systematic review.

BACKGROUND: Artificial intelligence has become part of healthcare with a multitude of applications being customized to roles required in clinical prac...

Hybrid attention-based deep learning for multi-label ophthalmic disease detection on fundus images.

BACKGROUND: Ophthalmic diseases significantly impact vision and quality of life. Early diagnosis using fundus images is critical for timely treatment....

A scoping review of artificial intelligence as a medical device for ophthalmic image analysis in Europe, Australia and America.

This scoping review aims to identify regulator-approved ophthalmic image analysis artificial intelligence as a medical device (AIaMD) in three jurisdi...

Complex Fractionated Atrial Electrograms, Dispersion, and Voltage in Persistent Atrial Fibrillation: Implications for Electrogram-Guided Ablation.

BACKGROUND: Various methods have been used to identify substrate of persistent atrial fibrillation (PeAF) including complex fractionated atrial electr...

Diagnosis and management of Candida endophthalmitis and chorioretinitis.

BACKGROUND: Candida endophthalmitis (CE) and chorioretinitis are uncommon but potentially devastating complications of candidemia, associated with sig...

A Deep Learning-Based Multimodal Fusion Model for Recurrence Prediction in Persistent Atrial Fibrillation Patients.

BACKGROUND: The long-term success rate of atrial fibrillation (AF) ablation remains a significant clinical challenge, particularly in patients with pe...

Machine learning-driven prediction of cycloplegic refractive error in Chinese children.

OBJECTIVE: To develop and validate machine learning (ML) models for predicting cycloplegic spherical equivalent refraction (SER) using non-cycloplegic...

Ophthalmic Image Synthesis and Analysis with Generative Adversarial Network Artificial Intelligence.

Generative adversarial networks (GANs), introduced by Ian Goodfellow in 2014, have revolutionized adversarial machine learning, particularly in data s...

An Artificial Intelligence Method for Phenotyping of OCT-Derived Thickness Maps Using Unsupervised and Self-supervised Deep Learning.

The objective of this study is to enhance the understanding of ophthalmic disease physiology and genetic architecture through the analysis of optical ...

Synergistic AI-resident approach achieves superior diagnostic accuracy in tertiary ophthalmic care for glaucoma and retinal disease.

INTRODUCTION: Artificial intelligence (AI) shows promise in ophthalmology, but its potential in tertiary care settings in Latin America remains unders...

Nystagmus in Clinical Practice: From Diagnosis to Treatment-A Comprehensive Review.

Nystagmus, a common yet intricate ocular movement disorder, significantly contributes to visual morbidity in the paediatric and adult populations. Def...

Applications, Ethical Considerations, and Patient Perspectives on Artificial Intelligence in Dermatologic Surgery: Focus on Mohs Surgery.

BACKGROUND: Artificial intelligence (AI) is increasingly used in health care and has the potential to revolutionize Mohs micrographic surgery (MMS) by...

Unsupervised Clustering of Patients Undergoing Thoracoscopic Ablation Identifies Relevant Phenotypes for Advanced Atrial Fibrillation.

: The rate of recurrence after ablation for atrial fibrillation (AF) is considerable. Risk stratification for AF recurrence after ablation remains inc...

Transfer Learning and Multi-Feature Fusion-Based Deep Learning Model for Idiopathic Macular Hole Diagnosis and Grading from Optical Coherence Tomography Images.

BACKGROUND: Idiopathic macular hole is an ophthalmic disease that seriously affects vision, and its early diagnosis and treatment have important clini...

A monocular endoscopic image depth estimation method based on a window-adaptive asymmetric dual-branch Siamese network.

Minimally invasive surgery involves entering the body through small incisions or natural orifices, using a medical endoscope for observation and clini...

Exploring the Role of Sodium Dodecyl Sulfate Surfactant in Enhancing the Fluorescence Properties of Besifloxacin Fluoroquinolone; Application to Eye Formulations and Artificial Aqueous Humor.

An ultrasensitive, selective, rapid, and cost-effective spectrofluorimetric approach is established and validated to quantify the ophthalmic fluoroqui...

Machine learning models for predicting survival in lung cancer patients undergoing microwave ablation.

OBJECTIVE: To develop and validate predictive models assessing survival outcomes in patients with non-small cell lung cancer (NSCLC) treated with micr...