Supporting inter-topic entity search for biomedical Linked Data based on heterogeneous relationships
The keyword-based entity search restricts search space based on the preference of search. When given keywords and preferences are not related to the same biomedical topic, existing biomedical Linked Data search engines fail to deliver satisfactory results. This research aims to tackle this issue by supporting an inter-topic search —improving search with inputs, keywords and preferences, under different topics. (Source: Computers in Biology and Medicine)
Source: Computers in Biology and Medicine - May 31, 2017 Category: Bioinformatics Authors: Nansu Zong, Sungin Lee, Jinhyun Ahn, Hong-Gee Kim Source Type: research
Noisy EEG signals classification based on entropy metrics. Performance assessment using first and second generation statistics
This paper evaluates the performance of first generation entropy metrics, featured by the well known and widely used Approximate Entropy (ApEn) and Sample Entropy (SampEn) metrics, and what can be considered an evolution from these, Fuzzy Entropy (FuzzyEn), in the Electroencephalogram (EEG) signal classification context. The study uses the commonest artifacts found in real EEGs, such as white noise, and muscular, cardiac, and ocular artifacts. Using two different sets of publicly available EEG records, and a realistic range of amplitudes for interfering artifacts, this work optimises and assesses the robustness of these me...
Source: Computers in Biology and Medicine - May 31, 2017 Category: Bioinformatics Authors: David Cuesta –Frau, Pau Miró–Martínez, Jorge Jordán Núñez, Sandra Oltra–Crespo, Antonio Molina Picó Source Type: research
Continuous lung region segmentation from endoscopic images for intra-operative navigation
Although preoperative Computed tomography images are widely used in intraoperative navigation, they can not provide precise information for organs such as the lungs, which deform severely during surgery because of deflation. By segmenting lung regions using intraoperative endoscopic images, a more accurate navigation can be obtained because endoscopic images directly provide real-time organ descriptions. However, satisfactory segmentation is rarely achieved with the algorithms in the literature due to the high deformability of the lungs and similarity between the background and object. (Source: Computers in Biology and Medicine)
Source: Computers in Biology and Medicine - May 31, 2017 Category: Bioinformatics Authors: Shuqiong Wu, Megumi Nakao, Tetsuya Matsuda Source Type: research
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Source: Computers in Biology and Medicine - May 30, 2017 Category: Bioinformatics Source Type: research
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Source: Computers in Biology and Medicine - May 30, 2017 Category: Bioinformatics Source Type: research
A new near-lossless EEG compression method using ANN-based reconstruction technique
Compression algorithm is an essential part of Telemedicine systems, to store and transmit large amount of medical signals. Most of existing compression methods utilize fixed transforms such as DCT and wavelet and usually cannot efficiently extract signal redundancy especially for non-stationary signals such as EEG. In this paper, we first propose learning-based adaptive transform using combination of DCT and artificial neural network (ANN) reconstruction technique. This adaptive ANN-based transform is applied to the DCT coefficients of EEG data to reduce its dimensionality and also to estimate the original DCT coefficients...
Source: Computers in Biology and Medicine - May 24, 2017 Category: Bioinformatics Authors: Behzad Hejrati, Abdolhossein Fathi, Fardin Abdali-Mohammadi Source Type: research
Analysis of the pen pressure and grip force signal during basic drawing tasks: The timing and speed changes impact drawing characteristics
Writing is a complex fine and trained motor skill, involving complex biomechanical and cognitive processes. In this paper, we propose the study of writing kinetics using three angles: the pen-tip normal force, the total grip force signal and eventually writing quality assessment. In order to collect writing kinetics data, we designed a sensor collecting these characteristics simultaneously. Ten healthy right-handed adults were recruited and were asked to perform four tasks: first, they were instructed to draw circles at a speed they considered comfortable; they then were instructed to draw circles at a speed they regarded ...
Source: Computers in Biology and Medicine - May 22, 2017 Category: Bioinformatics Authors: Arthur Gatouillat, Antoine Dumortier, Subashan Perera, Youakim Badr, Claudine Gehin, Ervin Sejdi ć Source Type: research
High-frequency power within the QRS complex in ischemic cardiomyopathy patients with ventricular arrhythmias: Insights from a clinical study and computer simulation of cardiac fibrous tissue
This study aimed to investigate the DFP within the QRS in ischemic cardiomyopathy (ICM) with lethal ventricular arrhythmias (L-VA). A computer simulation was performed to explore the mechanism of abnormal frequency power. (Source: Computers in Biology and Medicine)
Source: Computers in Biology and Medicine - May 22, 2017 Category: Bioinformatics Authors: Takeshi Tsutsumi, Yoshiwo Okamoto, Nami Takano, Daisuke Wakatsuki, Takanobu Tohmaru, Toshiaki Nakajima Source Type: research
Exploring syndrome differentiation using non-negative matrix factorization and cluster analysis in patients with atopic dermatitis
Syndrome differentiation (SD) results in a diagnostic conclusion based on a cluster of concurrent symptoms and signs, including pulse form and tongue color. In Korea, there is a strong interest in the standardization of Traditional Medicine (TM). In order to standardize TM treatment, standardization of SD should be given priority. The aim of this study was to explore the SD, or symptom clusters, of patients with atopic dermatitis (AD) using non-negative factorization methods and k-means clustering analysis. (Source: Computers in Biology and Medicine)
Source: Computers in Biology and Medicine - May 22, 2017 Category: Bioinformatics Authors: Younghee Yun, Wonmo Jung, Hyunho Kim, Bo-Hyoung Jang, Min-Hee Kim, Jiseong Noh, Seong-Gyu Ko, Inhwa Choi Source Type: research
Optimal design of nanowire field-effect troponin sensors
We propose a design strategy for affinity-based biosensors using nanowires for sensing and measuring biomarker concentration in biological samples. Such sensors have been shown to have superior properties compared to conventional biosensors in terms of LOD (limit of detection), response time, cost, and size. However, there are several parameters affecting the performance of such devices that must be determined. In order to solve the design problem, we have developed a comprehensive model based on stochastic transport equations that makes it possible to optimize the sensing behavior. (Source: Computers in Biology and Medicine)
Source: Computers in Biology and Medicine - May 20, 2017 Category: Bioinformatics Authors: Amirreza Khodadadian, Kiarash Hosseini, Ali Manzour-ol-Ajdad, Marjan Hedayati, Reza Kalantarinejad, Clemens Heitzinger Source Type: research
Multi-resolution classification of exhaled aerosol images to detect obstructive lung diseases in small airways
The objective of this study is to develop a simulation-based classification model that can accurately classify small airway diseases. The model performance was evaluated in five obstructed models that are located in lung bifurcations G7-9. (Source: Computers in Biology and Medicine)
Source: Computers in Biology and Medicine - May 20, 2017 Category: Bioinformatics Authors: Jinxiang Xi, Weizhong Zhao, Jiayao Eddie Yuan, Biwei Cao, Linlin Zhao Source Type: research
Simulation, identification and statistical variation in cardiovascular analysis (SISCA) – A software framework for multi-compartment lumped modeling
It has not yet been possible to obtain modeling approaches suitable for covering a wide range of real world scenarios in cardiovascular physiology because many of the system parameters are uncertain or even unknown. Natural variability and statistical variation of cardiovascular system parameters in healthy and diseased conditions are characteristic features for understanding cardiovascular diseases in more detail.This paper presents SISCA, a novel software framework for cardiovascular system modeling and its MATLAB implementation. (Source: Computers in Biology and Medicine)
Source: Computers in Biology and Medicine - May 20, 2017 Category: Bioinformatics Authors: Rudolf Huttary, Leonid Goubergrits, Christof Sch ütte, Stefan Bernhard Source Type: research
Spotting L3 slice in CT scans using deep convolutional network and transfer learning
In this article, we present a complete automated system for spotting a particular slice in a complete 3D Computed Tomography exam (CT scan). Our approach does not require any assumptions on which part of the patient's body is covered by the scan. It relies on an original machine learning regression approach. Our models are learned using the transfer learning trick by exploiting deep architectures that have been pre-trained on imageNet database, and therefore it requires very little annotation for its training. (Source: Computers in Biology and Medicine)
Source: Computers in Biology and Medicine - May 19, 2017 Category: Bioinformatics Authors: Soufiane Belharbi, Cl ément Chatelain, Romain Hérault, Sébastien Adam, Sébastien Thureau, Mathieu Chastan, Romain Modzelewski Source Type: research
Parallel gene selection and dynamic ensemble pruning based on Affinity Propagation
Gene selection and sample classification based on gene expression data are important research areas in bioinformatics. Selecting important genes closely related to classification is a challenging task due to high dimensionality and small sample size of microarray data. Extended rough set based on neighborhood has been successfully applied to gene selection, as it can select attributes without redundancy and deal with numerical attributes directly. However, the computation of approximations in rough set is extremely time consuming. (Source: Computers in Biology and Medicine)
Source: Computers in Biology and Medicine - May 17, 2017 Category: Bioinformatics Authors: Jun Meng, Jing Zhang, Yu-Shi Luan, Xin-Yu He, Li-Shuang Li, Yuan-Feng Zhu Source Type: research
ARIANNA: A research environment for neuroimaging studies in autism spectrum disorders
The complexity and heterogeneity of Autism Spectrum Disorders (ASD) require the implementation of dedicated analysis techniques to obtain the maximum from the interrelationship among many variables that describe affected individuals, spanning from clinical phenotypic characterization and genetic profile to structural and functional brain images. The ARIANNA project has developed a collaborative interdisciplinary research environment that is easily accessible to the community of researchers working on ASD (https://arianna.pi.infn.it). (Source: Computers in Biology and Medicine)
Source: Computers in Biology and Medicine - May 17, 2017 Category: Bioinformatics Authors: Alessandra Retico, Silvia Arezzini, Paolo Bosco, Sara Calderoni, Alberto Ciampa, Simone Coscetti, Stefano Cuomo, Luca De Santis, Dario Fabiani, Maria Evelina Fantacci, Alessia Giuliano, Enrico Mazzoni, Pietro Mercatali, Giovanni Miscali, Massimiliano Pard Source Type: research
