PURPOSE: Lumbosacral nerve root anomalies are relatively rare but can be a risk factor for intraoperative nerve injury. However, it is often difficult to evaluate them with preoperative imaging. We developed a software that automatically generates th...
Journal of refractive surgery (Thorofare, N.J. : 1995)
Mar 1, 2025
PURPOSE: To report a deep learning neural network on anterior segment optical coherence tomography (AS-OCT) for automated detection of different keratorefractive laser surgeries-including laser in situ keratomileusis with femtosecond microkeratome (f...
BACKGROUND: Several commercial programs incorporate artificial intelligence in diagnosis, but very few dental professionals have been surveyed regarding its acceptability and usability. Furthermore, few have explored how these advances might be incor...
This study aimed to develop an interpretable machine learning model to predict methylene blue (MB) responsiveness in adult patients with refractory septic shock and to identify key factors influencing MB responsiveness using the SHapley Additive exPl...
AIMS: Adult spinal deformity (ASD) surgery can reduce pain and disability. However, the actual surgical efficacy of ASD in doing so is far from desirable, with frequent complications and limited improvement in quality of life. The accurate prediction...
International journal of surgery (London, England)
Mar 1, 2025
OBJECTIVES: This study aimed to develop an artificial intelligence-assisted model for the preoperative prediction of lateral cervical lymph node metastasis (LCLNM) in papillary thyroid carcinoma (PTC) using computed tomography (CT) radiomics, providi...
PURPOSE: With the increasing utilization of endoscopic approaches for primary benign orbital tumor (PBOT) surgery, otolaryngologists and ophthalmologists are challenged with determining candidacy for endoscopic resection based on preoperative imaging...
Neural networks : the official journal of the International Neural Network Society
Feb 28, 2025
Objective classification biomarkers that are developed using resting-state functional magnetic resonance imaging (rs-fMRI) data are expected to contribute to more effective treatment for psychiatric disorders. Unfortunately, no widely accepted biomar...
RATIONALE AND OBJECTIVES: To generate virtual T1 contrast-enhanced (T1CE) sequences from plain spinal MRI sequences using the denoising diffusion probabilistic model (DDPM) and to compare its performance against one baseline model pix2pix and three a...
OBJECTIVE: This study aims to investigate the exosome-derived metabolomics profiles in systemic lupus erythematosus (SLE), identify differential metabolites, and analyze their potential as diagnostic markers for SLE and lupus nephritis (LN).
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