Laser Surgery

Machine learning-based clustering differentiates bilateral hepatocellular carcinoma characteristics and prognosis.

BACKGROUND: Bilateral hepatocellular carcinoma represents a biologically heterogeneous disease with uncertain optimal surgical selection criteria. Although hepatic resection can provide survival benefit in selected patients, outcomes remain variable, and phenotypic determinants of prognosis have not been clearly defined. METHODS: Patients who underwent curative-intent hepatectomy for bilateral hep...

MaxGRNet: A multi-axis vision transformer with improved generalization for eye disease classification using explainable AI with insertion-deletion operations on fundus images.

Eye diseases, including diabetic retinopathy (DR), glaucoma, and cataracts, represent a major global health concern and can lead to severe visual impairment or blindness if not identified in a timely manner. This study proposes a novel eye disease classification framework based on a multi-axis vision transformer (MaxViT) applied to color fundus images with Explainable Artificial Intelligence (XAI)...

[Large language models as a communication and organizational infrastructure in urology: evidence, limitations, and clinical responsibility].

Large language models (LLMs) mark a structural turning point in digital medicine, as they are now capable not only of processing medical information b...

AI-assisted diagnosis of neuro-ophthalmic disorders: a systematic review from optic neuritis to papilledema.

Deep Learning-based Segmentation for Assessment of Kidney Tumour Ablation Therapy in CT Images.

Kidney tumor ablation is a minimally invasive treatment for Renal Cell Carcinoma (RCC). Manual segmentation of the kidney ablation zone (KAZ) is time-...

Deep Learning Driven Evaluation of MR-guided Focused Ultrasound Ablation.

OBJECTIVE: Magnetic resonance-guided focused ultrasound (MRgFUS) thermal therapy is a promising incisionless procedure for breast cancer treatment. fo...

Clinical implementation of 3D deep learning techniques in predicting touch-up lesions for atrial fibrillation patients undergoing cryoablation.

BACKGROUND: Atrial fibrillation (AF) is a common heart rhythm disorder that can be treated with cryoballoon ablation (CBA). CBA occasionally requires ...

The WISeR Model and its Potential Impacts on Dermatologic Care.

Machine Learning Optimization of Laser Ablation in Liquid for the Green and Low-Cost Synthesis of Clean Gold Nanoparticles.

While gold nanoparticles (Au NPs) are widely employed in modern technology, their large-scale synthesis still faces challenges related to cost and sus...

Serum Uric Acid-to-Creatinine Ratio and Atherogenic Index of Plasma as Independent Prognostic Indicators for Late Non-Valvular Atrial Fibrillation Recurrence After Catheter Ablation.

BACKGROUND: Atrial fibrillation (AF) is one of the most common clinical arrhythmias, and postoperative recurrence remains a major concern in cardiovas...

LA-TReQNet: Improving Multielement Quantification Model for Laser Ablation Inductively Coupled Plasma Mass Spectrometry Based on Deep Learning Network.

Laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) is a widely used quantitative technique. However, conventional calibration app...

Image-Based Medical Navigation Systems for Cardiac Interventions: Recent Technological Advances.

BACKGROUND: The application of catheter-based treatments for a growing range of structural heart diseases (SHD) has significantly increased over the p...

A Deep Learning Prognostic Model for Diabetes Patients Using Bilateral Fundus Imaging.

AIMS: Diabetes mellitus shortens life expectancy, driven primarily by premature mortality from vascular complications. Mortality models for intensive ...

Improving support and self-management of ophthalmic patients using an artificial intelligence health coach.

This study evaluates patient engagement and satisfaction with Everyday Medical Monitoring Ally (E.M.M.A), a purpose-trained artificial intelligence (A...

[Correction of refractive errors by subtractive corneal surgery: History and perspectives].

The goal of this review is to trace the history of refractive correction, from the earliest optical devices to modern refractive surgical techniques. ...

Boosting foundation models for rare eye disease diagnosis via a multimodal text-to-image generative framework.

The rising prevalence of vision-threatening retinal diseases poses a significant burden on the global healthcare systems. Though deep learning (DL) te...

Exploring Deep Learning Models for Small Histopathology Datasets: Segmentation and Classification of Glomerular Crescent Lesions with Ablation, Interpretability, and Calibration Analyses.

Glomerular crescent lesions are critical indicators of severe kidney injury and are closely associated with disease progression. However, their automa...

Comprehensive Evaluation of ChatGPT's Diagnostic Accuracy on Image-based Ophthalmic Case Interpretations.

OBJECTIVE: To evaluate the diagnostic and treatment accuracy of Chat Generative Pre-trained Transformer (GPT-4.o) in ophthalmology, comparing performa...

Fuzzy logic for preanesthetic risk assessment in cataract surgery patients.

We aimed to build a fuzzy logic preanaesthetic risk score tailored to cataract surgery. By fusing systemic comorbidities with key patient attributes i...

Discrimination of vascular proliferation in eyelid surgery using multimodal hyperspectral imaging technology.

BACKGROUND AND OBJECTIVE: Vascular proliferation is a common skin reaction following eyelid surgery, and early diagnosis is crucial for improving trea...