BACKGROUND: Cardiovascular outcomes for people with familial hypercholesterolaemia can be improved with diagnosis and medical management. However, 90% of individuals with familial hypercholesterolaemia remain undiagnosed in the USA. We aimed to accel...
Journal of clinical neuroscience : official journal of the Neurosurgical Society of Australasia
Oct 21, 2019
The identification of high-grade glioma (HGG) progression may pose a diagnostic dilemma due to similar appearances of treatment-related changes (TRC) (e.g. pseudoprogression or radionecrosis). Deep learning (DL) may be able to assist with this task. ...
Machine learning has the potential to identify novel biological factors underlying successful antibody responses to influenza vaccines. The first attempts have revealed a high level of complexity in establishing influenza immunity, and many different...
Computational and mathematical methods in medicine
Oct 20, 2019
Motion artifacts and myoelectrical noise are common issues complicating the collection and processing of dynamic electrocardiogram (ECG) signals. Recent signal quality studies have utilized a binary classification metric in which ECG samples are dete...
Scandinavian cardiovascular journal : SCJ
Oct 18, 2019
In heart failure, invasive angiography is often employed to differentiate ischaemic from non-ischaemic cardiomyopathy. We aim to examine the predictive value of echocardiographic strain features alone and in combination with other features to differ...
BACKGROUND: Deep brain stimulation (DBS) surgery is an option for patients experiencing medically resistant neurologic symptoms. DBS complications are rare; finding significant predictors requires a large number of surgeries. Machine learning algorit...
Background and Purpose- The purpose of this study was to investigate the effects of gait training with a newly developed wearable hip-assist robot on locomotor function and efficiency in patients with chronic stroke. Methods- Twenty-eight patients wi...
Deep learning (DL) neural networks have only recently been employed to interpret chest radiography (CXR) to screen and triage people for pulmonary tuberculosis (TB). No published studies have compared multiple DL systems and populations. We conducted...
PURPOSE: This study sought to establish a robust and fully automated Type B aortic dissection (TBAD) segmentation method by leveraging the emerging deep learning techniques.
BACKGROUND: Current lung cancer screening guidelines use mean diameter, volume or density of the largest lung nodule in the prior computed tomography (CT) or appearance of new nodule to determine the timing of the next CT. We aimed at developing a mo...
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