Latest AI and machine learning research in laser surgery for healthcare professionals.
OBJECTIVE: Standard Automated Perimetry (SAP) is the primary method for monitoring glaucoma progression and an established functional endpoint in clinical trials. A ≥7 dB loss in at least five prespecified test locations has been proposed as a potential endpoint for glaucoma trials, but identifying such vulnerable points in advance remains a major challenge. We developed an artificial intelligence...
Access to eye care remains a global health priority, particularly for underserved populations in rural, Indigenous, and low-income communities. Despit...
Conventional skin imaging modalities are often bulky, expensive, and impractical for routine dermatology practice. There is a need for a portable, mul...
PURPOSE: To conduct a comprehensive systematic evaluation of federated learning (FL) strategies for multi-disease retinal classification using OCT ang...
To achieve high-performance qualitative and quantitative joint analysis of milk powder adulteration, a Multi-Task Mixture-of-Experts Convolutional Neu...
BACKGROUND: Existing models that use clinical history and cardiac imaging data remain inadequate for accurate prediction of the success of catheter ab...
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...