Laser Surgery

AI-assisted ophthalmic imaging for early detection of neurodegenerative diseases.

BACKGROUND: Artificial intelligence (AI) plays a promising role in ophthalmic imaging by providing innovative, non-invasive tools for the early detection of neurodegenerative diseases such as Alzheimer's disease (AD) and Parkinson's disease (PD). Since early diagnosis is crucial for slowing disease progression and improving patient outcomes, leveraging AI-assisted ophthalmic imaging retinal imagin...

Keypoint localization and parameter measurement in ultrasound biomicroscopy anterior segment images based on deep learning.

BACKGROUND: Accurate measurement of anterior segment parameters is crucial for diagnosing and managing ophthalmic conditions, such as glaucoma, cataracts, and refractive errors. However, traditional clinical measurement methods are often time-consuming, labor-intensive, and susceptible to inaccuracies. With the growing potential of artificial intelligence in ophthalmic diagnostics, this study aims...

Multi-objective optimization framework to plan laser ablation procedure for prostate tumors through a genetic algorithm.

BACKGROUND AND OBJECTIVES: Prostate cancer is the most common form of cancer in the male population. While the survival rate is high, many patients un...

Predicting Visual Acuity after Retinal Vein Occlusion Anti-VEGF Treatment: Development and Validation of an Interpretable Machine Learning Model.

Accurate prediction of post-treatment visual acuity in macular edema secondary to retinal vein occlusion (RVO-ME) is critical for optimizing anti-VEGF...

Retinal Ischemic Perivascular Lesions (RIPLs) as Potential Biomarkers for Systemic Vascular Diseases: A Narrative Review of the Literature.

Retinal ischemic perivascular lesions (RIPLs) are characteristic focal thinning of the inner nuclear layer, with an upward expansion of the outer nucl...

Sustaining Ophthalmic Practices for the Future: A High-Value Care Approach to Environmental Responsibility.

Ophthalmology, like all medical specialities, is continuously evolving to adapt to emerging challenges and advancements. The evidence-based medical pr...

Leveraging advanced graph neural networks for the enhanced classification of post anesthesia states to aid surgical procedures.

Anesthesia plays a pivotal role in modern surgery by facilitating controlled states of unconsciousness. Precise control is crucial for safe and pain-f...

Development of a Low-Profile, Piezoelectric Robot for MR-Guided Abdominal Needle Interventions.

PURPOSE: Minimally invasive needle-based interventions are commonly used in cancer diagnosis and treatment, including procedures, such as biopsy, brac...

Multimodal Performance of GPT-4 in Complex Ophthalmology Cases.

The integration of multimodal capabilities into GPT-4 represents a transformative leap for artificial intelligence in ophthalmology, yet its utility ...

Improved Solubility Predictions in scCO Using Thermodynamics-Informed Machine Learning Models.

Accurate solubility prediction in supercritical carbon dioxide (scCO) is crucial for optimizing experimental design by eliminating unnecessary and cos...

Predicting the efficacy of microwave ablation of benign thyroid nodules from ultrasound images using deep convolutional neural networks.

BACKGROUND: Thyroid nodules are frequent in clinical settings, and their diagnosis in adults is growing, with some persons experiencing symptoms. Ultr...

Enhancing Ophthalmic Anesthesia Optimization with Predictive Embedding Models.

Ophthalmic anesthesia the crucial factors in success and safety of ophthalmic surgery, which involves the delicate aspects of pain control, sedation, ...

Retinal OCT image segmentation with deep learning: A review of advances, datasets, and evaluation metrics.

Optical coherence tomography (OCT) is a widely used imaging technology in ophthalmic clinical practice, providing non-invasive access to high-resoluti...

Triage of Patient Messages Sent to the Eye Clinic via the Electronic Medical Record: A Comparative Study on AI and Human Triage Performance.

: Assess the ability of ChatGPT-4 (GPT-4) to effectively triage patient messages sent to the general eye clinic at our institution. : Patient messages...

A prediction model based on machine learning: prognosis of HBV-induced HCC male patients with smoking and drinking habits after local ablation treatment.

BACKGROUND: Liver cancer, particularly hepatocellular carcinoma (HCC), is a major health concern globally and in China, possibly shows recurrence afte...

Machine learning models for prediction of NPVR ≥80% with HIFU ablation for uterine fibroids.

BACKGROUND: Currently high-intensity focused ultrasound (HIFU) is widely used to treat uterine fibroids (UFs). The aim of this study is to develop a m...

The impact of training image quality with a novel protocol on artificial intelligence-based LGE-MRI image segmentation for potential atrial fibrillation management.

BACKGROUND: Atrial fibrillation (AF) is the most common cardiac arrhythmia, affecting up to 2 % of the population. Catheter ablation is a promising tr...

Use and Usefulness of Risk Prediction Tools in Urologic Surgery: Current State and Path Forward.

INTRODUCTION: Although the enthusiasm for artificial intelligence (AI) to enhance surgical decision-making continues to grow, the preceding advance of...

Integration of novel artificial intelligence tools in pediatric urologic practice.

PURPOSE OF REVIEW: There has been an explosion of creative uses of artificial intelligence (AI) in healthcare, with AI being touted as a solution for ...

D-GET: Group-Enhanced Transformer for Diabetic Retinopathy Severity Classification in Fundus Fluorescein Angiography.

Early detection of Diabetic Retinopathy (DR) is vital for preserving vision and preventing deterioration of eyesight. Fundus Fluorescein Angiography (...