BACKGROUND: Deep learning (DL) reconstruction techniques have shown promise in reducing MRI acquisition times while maintaining image quality. However, the impact of different acceleration factors on diagnostic accuracy in shoulder MRI remains unexpl...
INTRODUCTION: Artificial Intelligence (AI) modules might simplify the complexities of cardiac ultrasound (US) training by offering real-time, step-by-step guidance on probe manipulation for high-quality diagnostic imaging. This study investigates rea...
BACKGROUND: The American Heart Association recently introduced the concept of cardiovascular-kidney-metabolic (CKM) syndrome, highlighting the increasing importance of the complex interplay between metabolic, renal, and cardiovascular diseases (CVD)....
OBJECTIVES: To validate clinical scores [Testicular Workup for Ischemia and Suspected Torsion (TWIST), testicular torsion (TT) score, Artificial Intelligence-based Score (AIS), Boettcher Alert Score (BALS)] when evaluating children under 18 with non-...
The opioid overdose epidemic has rapidly expanded in North America, with rates accelerating during the COVID-19 pandemic. No existing study has demonstrated prospective opioid overdose at a population level. This study aimed to develop and validate a...
The journal of trauma and acute care surgery
Apr 14, 2025
BACKGROUND: The Rib Fracture Frailty (RFF) Index is an internally validated machine learning-based risk assessment tool for adult patients with rib fractures that requires minimal provider entry. Existing frailty risk scores have yet to undergo head-...
The precise and efficient diagnosis of an individual's skeletal class is necessary in orthodontics to ensure correct and stable treatment planning. However, it is difficult to efficiently determine the true skeletal class due to several correlations ...
OBJECTIVE: Compare the image quality of image reconstructed using deep learning-based image reconstruction (DLIR) and iterative reconstruction algorithms for head and neck dual-energy CT angiography (DECTA).
UNLABELLED: This study aimed to develop and validate a risk prediction model for moderate to severe bleeding in children with immune thrombocytopenia (ITP). Data from 286 ITP patients were prospectively collected and randomly split into training (80%...
To investigate the potential of employing artificial intelligence (AI) -driven breast ultrasound analysis models for the classification of glandular tissue components (GTC) in dense breast tissue. A total of 1,848 healthy women with mammograms classi...
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