BACKGROUND AND AIMS: We aimed to identify a blood-based gene expression score (GES) to predict the severity of coronary artery stenosis in patients with known or suspected coronary artery disease (CAD) by integrative use of gene network construction,...
BACKGROUND: Although some studies show that there could be a genetic predisposition to develop Multiple Sclerosis (MS), attempts to find genetic signatures related to MS diagnosis and development are extremely rare.
Routine blood test results are assumed to contain much more information than is usually recognised even by the most experienced clinicians. Using routine blood tests from 15,176 neurological patients we built a machine learning predictive model for t...
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Oct 8, 2019
It is well known that most patients with Parkinson's disease (PD) have different degree of movement disorders, such as shuffling, festination and akinetic episodes, which could degenerate the life quality of PD patients. Therefore, it is very useful ...
BACKGROUND: Predicting sex is an important problem in forensic medicine. The femur, patella, mandible and calcaneus bones are frequently used in predicting sex. In our study, we aimed to use the artificial neural network (ANN) technique to predict se...
Background Men suspected of having clinically significant prostate cancer (sPC) increasingly undergo prostate MRI. The potential of deep learning to provide diagnostic support for human interpretation requires further evaluation. Purpose To compare t...
One of the main technical challenges of PET/MRI is to achieve an accurate PET attenuation correction (AC) estimation. In current systems, AC is accomplished by generating an MRI-based surrogate computed tomography (CT) from which AC-maps are derived....
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