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...
Support Vector Machine (SVM) has been shown to be an effective learning algorithm for classification and prediction. However, the application of SVM for prediction and classification in specific sport has rarely been used to quantify/discriminate low...
Increasing manufacture and usage of chemicals have not been matched by the increase in our understanding of their risks. Pollutant release and transfer register (PRTR) is becoming a popular measure for collecting chemical data and enhancing the publi...
Computer methods and programs in biomedicine
Dec 12, 2017
BACKGROUND: Breast cancer is the most common cancer affecting females worldwide. Breast cancer survivability prediction is challenging and a complex research task. Existing approaches engage statistical methods or supervised machine learning to asses...
The present study aimed to identify the feature genes associated with smoking in lung adenocarcinoma (LAC) samples and explore the underlying mechanism. Three gene expression datasets of LAC samples were downloaded from the Gene Expression Omnibus da...
Computer methods and programs in biomedicine
Dec 6, 2017
BACKGROUND AND OBJECTIVES: Schizophrenia is a severe brain disorder primarily diagnosed through externally observed behavioural symptoms due to the dearth of established clinical tests. Functional magnetic resonance imaging (fMRI) can capture the dis...
Modern multivariate methods have enabled the application of unsupervised techniques to analyze neurophysiological data without strict adherence to predefined experimental conditions. We demonstrate a multivariate method that leverages priming effects...
Mobile robotics is a potential solution to home behavior monitoring for the elderly. For a mobile robot in the real world, there are several types of uncertainties for its perceptions, such as the ambiguity between a target object and the surrounding...
AIMS: The objective of this study is to investigate the possibility of the neuromorphotopological clustering of neostriate interneurons (NSIN) and their consequent classification into caudate (CIN) and putaminal neuron type (PIN), according to the nu...
BACKGROUND: With the development of chromosomal conformation capturing techniques, particularly, the Hi-C technique, the study of the spatial conformation of a genome is becoming an important topic in bioinformatics and computational biology. The Hi-...