Latest AI and machine learning research in laser surgery for healthcare professionals.
To achieve high-performance qualitative and quantitative joint analysis of milk powder adulteration, a Multi-Task Mixture-of-Experts Convolutional Neural Network (MTMoE-CNN) based on time-resolved laser-induced breakdown spectroscopy (LIBS) was proposed. In this method, through the integration of a temporal convolutional network and an adaptive Inception module, both local spectral details and glo...
BACKGROUND: Existing models that use clinical history and cardiac imaging data remain inadequate for accurate prediction of the success of catheter ablation for atrial fibrillation (AF). Local strain in the left atrium (LA) from 4-dimensional computed tomography (4DCT) has potential to add value to models of ablation outcome. OBJECTIVE: This study aimed to investigate whether local LA strain from ...
By 2050, advances in artificial intelligence (AI), Internet of Medical Things (IoMT) and teledermatology are predicted to fundamentally transform the ...
BACKGROUND: Diagnosis of prostate cancer in the PSA gray zone (4-10Â ng/mL) and PI-RADS 3 cases remains challenging. Although multiparametric MRI (mpMR...
PURPOSE: Novel large language models (LLMs) such as Generative Pretrained Transformer-5 (GPT-5) integrate advanced reasoning capabilities that may enh...
UNLABELLED: Large language models (LLMs) are increasingly used in healthcare; however, their reliability is shaped not only by model design but also b...
Artificial intelligence (AI) is gradually altering urology by improving diagnostic precision, prognostic evaluation, and therapy decisions in a broad ...
BACKGROUND AND OBJECTIVE: Accurate intraoperative differentiation between focal nodular hyperplasia (FNH) and hepatocellular carcinoma (HCC) remains a...
PURPOSE: To develop and validate OCT-PRO, a multimodal machine learning model integrating OCT images and clinical traits to predict postoperative visu...
BACKGROUND: The TAILORED-AF randomized trial demonstrated that artificial intelligence-guided ablation of spatiotemporal dispersion in addition to pul...
BACKGROUND: Microwave ablation (MWA) is a minimally invasive treatment for liver tumors, yet accurate prediction of ablation zones remains challenging...
OBJECTIVE: Develop a deep learning model for automatic hepatocellular carcinoma (HCC) detection in T1 weighted imaging (WI) Dynamic Contrast-Enhanced ...
High-quality fundus images provide essential anatomical information for clinical screening and ophthalmic disease diagnosis. Yet, due to hardware limi...
BACKGROUND: Vision and vision-language foundation models, a subset of advanced artificial intelligence (AI) frameworks, have shown transformative pote...
OBJECTIVE: Aims to develop a standardized evaluation method based on the YOLOv8n object detection algorithm, with the goal of quantitatively assessing...
BACKGROUND: Large language models (LLMs) have gained prominence in medical applications, yet their performance in specialized clinical tasks remains u...
OBJECTIVE: To provide a comprehensive summary of the controlled-access Age-Related Eye Disease Study 2 (AREDS2) data elements, encompassing phenotypic...