BACKGROUND: Asthma is a complex, heterogeneous disorder with similar presenting symptoms but with varying underlying pathologies. Exhaled breath condensate (EBC) is a relatively unexplored matrix which reflects the signatures of respiratory epitheliu...
The fixed-size non-overlapping sliding window (FNSW) and fixed-size overlapping sliding window (FOSW) approaches are the most commonly used data-segmentation techniques in machine learning-based fall detection using accelerometer sensors. However, th...
Purpose To develop a deep learning algorithm that generates arterial spin labeling (ASL) perfusion images with higher accuracy and robustness by using a smaller number of subtraction images. Materials and Methods For ASL image generation from pair-wi...
BACKGROUND: The Experimental Factor Ontology (EFO) is an application ontology driven by experimental variables including cell lines to organize and describe the diverse experimental variables and data resided in the EMBL-EBI resources. The Cell Line ...
Oxygen-induced retinopathy (OIR) is a widely used model to study ischemia-driven neovascularization (NV) in the retina and to serve in proof-of-concept studies in evaluating antiangiogenic drugs for ocular, as well as nonocular, diseases. The primary...
Computational intelligence and neuroscience
Dec 21, 2017
With the advent of the -modes algorithm, the toolbox for clustering categorical data has an efficient tool that scales linearly in the number of data items. However, random initialization of cluster centers in -modes makes it hard to reach a good clu...
Segmenting human left ventricle (LV) in magnetic resonance imaging images and calculating its volume are important for diagnosing cardiac diseases. The latter task became the topic of the Second Annual Data Science Bowl organized by Kaggle. The datas...
In this work, a functional supervised learning scheme is proposed for the classification of subjects into normotensive and hypertensive groups, using solely the 24-hour blood pressure data, relying on the concepts of Fréchet mean and Fréchet variance...
Neural networks : the official journal of the International Neural Network Society
Dec 20, 2017
In this paper, we investigate a more general sparse signal recovery minimization model and a smoothing neural network optimal method for compress sensing problem, where the objective function is a L minimization model which includes nonsmooth, noncon...
Machine learning systems are achieving better performances at the cost of becoming increasingly complex. However, because of that, they become less interpretable, which may cause some distrust by the end-user of the system. This is especially importa...
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