The accurate and efficient segmentation of coronary arteries in X-ray angiograms represents an essential task for computer-aided diagnosis. This paper presents a new multiscale Gaussian-matched filter (MGMF) based on artificial neural networks. The p...
Online medical text is full of references to medical entities (MEs), which are valuable in many applications, including medical knowledge-based (KB) construction, decision support systems, and the treatment of diseases. However, the diverse and ambig...
This study evaluates and compares the performance of different machine learning techniques on predicting the individuals at risk of developing hypertension, and who are likely to benefit most from interventions, using the cardiorespiratory fitness da...
IEEE journal of biomedical and health informatics
Apr 17, 2018
Electronic health records have brought valuable improvements to hospital practices by integrating patient information. In fact, the understanding of these data can prevent mistakes that may put patients' lives at risk. Nonetheless, to the best of our...
Neural networks : the official journal of the International Neural Network Society
Apr 17, 2018
Deep learning algorithms achieve human-level (or better) performance on many tasks, but there still remain situations where humans learn better or faster. With regard to classification of images, we argue that some of those situations are because the...
The journal of physical chemistry letters
Apr 17, 2018
Predicting the activity of chemicals for a given odorant receptor is a longstanding challenge. Here the activity of 258 chemicals on the human G-protein-coupled odorant receptor (OR)51E1, also known as prostate-specific G-protein-coupled receptor 2 (...
We sought to investigate, whether texture analysis of diffusional kurtosis imaging (DKI) enhanced by support vector machine (SVM) analysis may provide biomarkers for gliomas staging and detection of the IDH mutation. First-order statistics and textur...
IEEE transactions on pattern analysis and machine intelligence
Apr 16, 2018
State-of-the-art face recognition systems are based on deep (convolutional) neural networks. Therefore, it is imperative to determine to what extent face templates derived from deep networks can be inverted to obtain the original face image. In this ...
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