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Computational and Mathematical Methods in Medicine

Alba Sedano-Capdevila, María Luisa Barrigón, David Delgado-Gomez, Igor Barahona, Fuensanta Aroca, Inmaculada Peñuelas-Calvo, Carolina Miguelez-Fernandez, Alba Rodríguez-Jover, Susana Amodeo-Escribano, Marta González-Granado, Enrique Baca-García
WHODAS 2.0 is the standard measure of disability promoted by World Health Organization whereas Clinical Global Impression (CGI) is a widely used scale for determining severity of mental illness. Although a close relationship between these two scales would be expected, there are no relevant studies on the topic. In this study, we explore if WHODAS 2.0 can be used for identifying severity of illness measured by CGI using the Fisher Linear Discriminant Analysis (FLDA) and for identifying which individual items of WHODAS 2...
2018: Computational and Mathematical Methods in Medicine
Mengxi Dai, Dezhi Zheng, Shucong Liu, Pengju Zhang
Motor-imagery-based brain-computer interfaces (BCIs) commonly use the common spatial pattern (CSP) as preprocessing step before classification. The CSP method is a supervised algorithm. Therefore a lot of time-consuming training data is needed to build the model. To address this issue, one promising approach is transfer learning, which generalizes a learning model can extract discriminative information from other subjects for target classification task. To this end, we propose a transfer kernel CSP (TKCSP) approach to learn a domain-invariant kernel by directly matching distributions of source subjects and target subjects...
2018: Computational and Mathematical Methods in Medicine
Baolin Wu, James S Pankow
Multiple correlated traits are often collected in genetic studies. By jointly analyzing multiple traits, we can increase power by aggregating multiple weak effects and reveal additional insights into the genetic architecture of complex human diseases. In this article, we propose a multivariate linear regression-based method to test the joint association of multiple quantitative traits. It is flexible to accommodate any covariates, has very accurate control of type I errors, and offers very competitive performance...
2018: Computational and Mathematical Methods in Medicine
Young Jae Kim, Kwang Gi Kim
Existing drusen measurement is difficult to use in clinic because it requires a lot of time and effort for visual inspection. In order to resolve this problem, we propose an automatic drusen detection method to help clinical diagnosis of age-related macular degeneration. First, we changed the fundus image to a green channel and extracted the ROI of the macular area based on the optic disk. Next, we detected the candidate group using the difference image of the median filter within the ROI. We also segmented vessels and removed them from the image...
2018: Computational and Mathematical Methods in Medicine
Xuefei Yu, Liangzhuo Lin, Jie Shen, Zhi Chen, Jun Jian, Bin Li, Sherman Xuegang Xin
The mean amplitude of glycemic excursions (MAGE) is an essential index for glycemic variability assessment, which is treated as a key reference for blood glucose controlling at clinic. However, the traditional "ruler and pencil" manual method for the calculation of MAGE is time-consuming and prone to error due to the huge data size, making the development of robust computer-aided program an urgent requirement. Although several software products are available instead of manual calculation, poor agreement among them is reported...
2018: Computational and Mathematical Methods in Medicine
Anam Mustaqeem, Syed Muhammad Anwar, Muahammad Majid
Arrhythmia is considered a life-threatening disease causing serious health issues in patients, when left untreated. An early diagnosis of arrhythmias would be helpful in saving lives. This study is conducted to classify patients into one of the sixteen subclasses, among which one class represents absence of disease and the other fifteen classes represent electrocardiogram records of various subtypes of arrhythmias. The research is carried out on the dataset taken from the University of California at Irvine Machine Learning Data Repository...
2018: Computational and Mathematical Methods in Medicine
Munenori Uemura, Morimasa Tomikawa, Tiejun Miao, Ryota Souzaki, Satoshi Ieiri, Tomohiko Akahoshi, Alan K Lefor, Makoto Hashizume
This study investigated whether parameters derived from hand motions of expert and novice surgeons accurately and objectively reflect laparoscopic surgical skill levels using an artificial intelligence system consisting of a three-layer chaos neural network. Sixty-seven surgeons (23 experts and 44 novices) performed a laparoscopic skill assessment task while their hand motions were recorded using a magnetic tracking sensor. Eight parameters evaluated as measures of skill in a previous study were used as inputs to the neural network...
2018: Computational and Mathematical Methods in Medicine
Teng Ma, Fali Li, Peiyang Li, Dezhong Yao, Yangsong Zhang, Peng Xu
Electroencephalogram signals and the states of subjects are nonstationary. To track changing states effectively, an adaptive calibration framework is proposed for the brain-computer interface (BCI) with the motion-onset visual evoked potential (mVEP) as the control signal. The core of this framework is to update the training set adaptively for classifier training. The updating procedure consists of two operations, that is, adding new samples to the training set and removing old samples from the training set...
2018: Computational and Mathematical Methods in Medicine
Rongyang Wang, Yikun Wei, Chuanyu Wu, Liang Sun, Wenguang Zheng
The immersed boundary-lattice Boltzmann method (IB-LBM) was used to examine the motion and deformation of three elastic red blood cells (RBCs) during Poiseuille flow through constricted microchannels. The objective was to determine the effects of the degree of constriction and the Reynolds (Re) number of the flow on the physical characteristics of the RBCs. It was found that, with decreasing constriction ratio, the RBCs experienced greater forced deformation as they squeezed through the constriction area compared to at other parts of the microchannel...
2018: Computational and Mathematical Methods in Medicine
Rui Mu, Youping Yang
An SEIR type of compartmental model with nonlinear incidence and recovery rates was formulated to study the combined impacts of psychological effect and available resources of public health system especially the number of hospital beds on the transmission and control of A(H7N9) virus. Global stability of the disease-free and endemic equilibria is determined by the basic reproduction number as a threshold parameter and is obtained by constructing Lyapunov function and second additive compound matrix. The results obtained reveal that psychological effect and available resources do not change the stability of the steady states but can indeed diminish the peak and the final sizes of the infected...
2018: Computational and Mathematical Methods in Medicine
Huisi Miao, Changyan Xiao
The density or quantity of leukocytes and erythrocytes in a unit volume of blood, which can be automatically measured through a computer-based microscopic image analysis system, is frequently considered an indicator of diseases. The segmentation of blood cells, as a basis of quantitative statistics, plays an important role in the system. However, many conventional methods must firstly distinguish blood cells into two types (i.e., leukocyte and erythrocyte) and segment them in independent procedures. In this paper, we present a marker-controlled watershed algorithm for simultaneously extracting the two types of blood cells to simplify operations and reduce computing time...
2018: Computational and Mathematical Methods in Medicine
Sarmad Shafique, Samabia Tehsin
Leukaemia is a form of blood cancer which affects the white blood cells and damages the bone marrow. Usually complete blood count (CBC) and bone marrow aspiration are used to diagnose the acute lymphoblastic leukaemia. It can be a fatal disease if not diagnosed at the earlier stage. In practice, manual microscopic evaluation of stained sample slide is used for diagnosis of leukaemia. But manual diagnostic methods are time-consuming, less accurate, and prone to errors due to various human factors like stress, fatigue, and so forth...
2018: Computational and Mathematical Methods in Medicine
Yung-Shin Sun
Tumor Treating Fields (TTFields) in combination with chemotherapy and/or radiotherapy have been clinically reported to provide prolonged overall survival in glioblastoma patients. Alternating electric fields with frequencies of 100~300 kHz and magnitudes of 1~3 V/cm are shown to suppress the growth of cancer cells via interactions with polar molecules within dividing cells. Since it is difficult to directly measure the electric fields inside the brain, simulation models of the human head provide a useful tool for predicting the electric field distribution...
2018: Computational and Mathematical Methods in Medicine
Tyler Nelson, Joon Jin Song, Yoo-Mi Chin, James D Stamey
Covariate misclassification is well known to yield biased estimates in single level regression models. The impact on hierarchical count models has been less studied. A fully Bayesian approach to modeling both the misclassified covariate and the hierarchical response is proposed. Models with a single diagnostic test and with multiple diagnostic tests are considered. Simulation studies show the ability of the proposed model to appropriately account for the misclassification by reducing bias and improving performance of interval estimators...
2018: Computational and Mathematical Methods in Medicine
Akbar Hassanzadeh, Zahra Heidari, Awat Feizi, Ammar Hassanzadeh Keshteli, Hamidreza Roohafza, Hamid Afshar, Payman Adibi
[This corrects the article DOI: 10.1155/2017/3457103.].
2018: Computational and Mathematical Methods in Medicine
Fei Li, Xinzhu Meng, Xinzeng Wang
This paper considers a high-dimensional stochastic SEIQR (susceptible-exposed-infected-quarantined-recovered) epidemic model with quarantine-adjusted incidence and the imperfect vaccination. The main aim of this study is to investigate stochastic effects on the SEIQR epidemic model and obtain its thresholds. We first obtain the sufficient condition for extinction of the disease of the stochastic system. Then, by using the theory of Hasminskii and the Lyapunov analysis methods, we show there is a unique stationary distribution of the stochastic system and it has an ergodic property, which means the infectious disease is prevalent...
2018: Computational and Mathematical Methods in Medicine
Yulin Zhang, Maoxian Zhao, Jionglong Su, Xiao Lu, Kebo Lv
A novel model for cascading failures in a directed logic network based on the degree strength at a node was proposed. The definitions of in-degree and out-degree strength of a node were initially reconsidered, and the load at a nonisolated node was proposed as the ratio of in-degree strength to out-degree strength of the node. The cascading failure model based on degree strength was applied to the logic network for three types of cancer including adenocarcinoma of lung, prostate cancer, and colon cancer based on their gene expression profiles...
2018: Computational and Mathematical Methods in Medicine
Omar Piña-Ramirez, Raquel Valdes-Cristerna, Oscar Yanez-Suarez
P300 spellers have been widely modified to implement nonspelling tasks. In this work, we propose a "scenario" stimulation screen that is a P300 speller variation to command a wheelchair. Our approach utilized a stimulation screen with an image background (scenario snapshot for a wheelchair) and stimulation markers arranged asymmetrically over relevant landmarks, such as suitable paths, doors, windows, and wall signs. Other scenario stimulation screen features were green/blue stimulation marker color scheme, variable Interstimulus Interval, single marker stimulus mode, and optimized stimulus sequence generator...
2018: Computational and Mathematical Methods in Medicine
Sangmin Seo, Jonghwan Choi, Soon Kil Ahn, Kil Won Kim, Jaekwang Kim, Jaehyuck Choi, Jinho Kim, Jaegyoon Ahn
We propose a novel method that predicts binding of G-protein coupled receptors (GPCRs) and ligands. The proposed method uses hub and cycle structures of ligands and amino acid motif sequences of GPCRs, rather than the 3D structure of a receptor or similarity of receptors or ligands. The experimental results show that these new features can be effective in predicting GPCR-ligand binding (average area under the curve [AUC] of 0.944), because they are thought to include hidden properties of good ligand-receptor binding...
2018: Computational and Mathematical Methods in Medicine
Jiucheng Xu, Huiyu Mu, Yun Wang, Fangzhou Huang
The selection of feature genes with high recognition ability from the gene expression profiles has gained great significance in biology. However, most of the existing methods have a high time complexity and poor classification performance. Motivated by this, an effective feature selection method, called supervised locally linear embedding and Spearman's rank correlation coefficient (SLLE-SC2 ), is proposed which is based on the concept of locally linear embedding and correlation coefficient algorithms. Supervised locally linear embedding takes into account class label information and improves the classification performance...
2018: Computational and Mathematical Methods in Medicine
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