Journal of magnetic resonance imaging : JMRI
May 24, 2023
BACKGROUND: Diagnostic performance of placenta accreta spectrum (PAS) by prenatal MRI is unsatisfactory. Deep learning radiomics (DLR) has the potential to quantify the MRI features of PAS.
AJR. American journal of roentgenology
May 24, 2023
Computer-aided diagnosis (CAD) systems for breast ultrasound interpretation have been primarily evaluated at tertiary and/or urban medical centers by radiologists with breast ultrasound expertise. The purpose of this study was to evaluate the usefu...
Journal of magnetic resonance imaging : JMRI
May 23, 2023
BACKGROUND: The delineation of brain arteriovenous malformations (bAVMs) is crucial for subsequent treatment planning. Manual segmentation is time-consuming and labor-intensive. Applying deep learning to automatically detect and segment bAVM might he...
While a robust literature on the psychology of conspiracy theories has identified dozens of characteristics correlated with conspiracy theory beliefs, much less attention has been paid to understanding the generalized predisposition towards interpret...
OBJECTIVE: This study aims to improve workers' postures and thus reduce the risk of musculoskeletal disorders in human-robot collaboration by developing a novel model-free reinforcement learning method.
OBJECTIVE: Robot-assisted (RA) stereotactic MRI-guided laser ablation has been reported to be a safe and effective technique for the treatment of epileptogenic foci in children and adults. In this study the authors aimed to assess the accuracy of RA ...
BACKGROUND: Recurrent graft fibrosis after liver transplantation can threaten both graft and patient survival. Therefore, early detection of fibrosis is essential to avoid disease progression and the need for retransplantation. Non-invasive blood-bas...
Journal of applied physiology (Bethesda, Md. : 1985)
May 18, 2023
Nonintrusive estimation of oxygen uptake (V̇o) is possible with wearable sensor technology and artificial intelligence. V̇o kinetics have been accurately predicted during moderate exercise using easy-to-obtain sensor inputs. However, V̇o prediction a...
BACKGROUND: Radiomics is the process of converting radiological images into high-dimensional data that may be used to create machine learning models capable of predicting clinical outcomes, such as disease progression, treatment response and survival...
OBJECTIVE: The study aims to evaluate the diagnostic performance of deep learning-based reconstruction method (DLRecon) in 3D MR neurography for assessment of the brachial and lumbosacral plexus.
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.