BACKGROUND: The treatment and care of adults and children with traumatic brain injury (TBI) constitute an intractable global health problem. Predicting the prognosis and length of hospital stay of patients with TBI may improve therapeutic effects and...
Journal of magnetic resonance (San Diego, Calif. : 1997)
Dec 8, 2022
Multi-contrast magnetic resonance imaging (MRI) can provide richer diagnosis information. The data acquisition time, however, is increased than single-contrast imaging. To reduce this time, k-space undersampling is an effective way but a smart recons...
IEEE/ACM transactions on computational biology and bioinformatics
Dec 8, 2022
Sepsis is a major public concern due to its high mortality, morbidity, and financial cost. There are many existing works of early sepsis prediction using different machine learning models to mitigate the outcomes brought by sepsis. In the practical s...
Acta radiologica (Stockholm, Sweden : 1987)
Dec 7, 2022
BACKGROUND: To assess low-contrast areas such as plaque and coronary artery stenosis, coronary computed tomography angiography (CCTA) needs to provide images with lower noise without increasing radiation doses.
BACKGROUND: Two of the most common foregut operations are laparoscopic Heller myotomy and laparoscopic Nissen fundoplication. Robotic assistance, compared to standard laparoscopic approach, may potentially grant surgeons advantages such as enhanced v...
OBJECTIVES: No method is available to determine the non-perfused volume (NPV) repeatedly during magnetic resonance-guided high-intensity focused ultrasound (MR-HIFU) ablations of uterine fibroids, as repeated acquisition of contrast-enhanced T1-weigh...
Background Perfusion imaging is important to identify a target mismatch in stroke but requires contrast agents and postprocessing software. Purpose To use a deep learning model to predict the hypoperfusion lesion in stroke and identify patients with ...
Background Supine chest radiography for bedridden patients in intensive care units (ICUs) is one of the most frequently ordered imaging studies worldwide. Purpose To evaluate the diagnostic performance of a neural network-based model that is trained ...
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