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Capacity Evaluation of Diagnostic Tests For COVID19 Using Multicriteria DecisionMaking Techniques Comput. Math. Method Med. (IF 1.77) Pub Date : 20200806
Murat Sayan; Figen Sarigul Yildirim; Tamer Sanlidag; Berna Uzun; Dilber Uzun Ozsahin; Ilker OzsahinIn December 2019, cases of pneumonia were detected in Wuhan, China, which were caused by the highly contagious coronavirus. This study is aimed at comparing the confusion regarding the selection of effective diagnostic methods to make a mutual comparison among existing SARSCoV2 diagnostic tests and at determining the most effective one. Based on available published evidence and clinical practice

An Automatic Epilepsy Detection Method Based on Improved Inductive Transfer Learning Comput. Math. Method Med. (IF 1.77) Pub Date : 20200803
Yufeng Yao; Zhiming CuiEpilepsy is a chronic disease caused by sudden abnormal discharge of brain neurons, causing transient brain dysfunction. The seizures of epilepsy have the characteristics of being sudden and repetitive, which has seriously endangered patients’ health, cognition, etc. In the current condition, EEG plays a vital role in the diagnosis, judgment, and qualitative location of epilepsy among the clinical

An EEG Database and Its Initial Benchmark Emotion Classification Performance Comput. Math. Method Med. (IF 1.77) Pub Date : 20200803
Ayan Seal; Puthi Prem Nivesh Reddy; Pingali Chaithanya; Arramada Meghana; Kamireddy Jahnavi; Ondrej Krejcar; Radovan HudakHuman emotion recognition has been a major field of research in the last decades owing to its noteworthy academic and industrial applications. However, most of the stateoftheart methods identified emotions after analyzing facial images. Emotion recognition using electroencephalogram (EEG) signals has got less attention. However, the advantage of using EEG signals is that it can capture real emotion

Mathematical Model for Optimal Control of SoilTransmitted Helminth Infection Comput. Math. Method Med. (IF 1.77) Pub Date : 20200801
Aristide G. Lambura; Gasper G. Mwanga; Livingstone Luboobi; Dmitry KuznetsovIn this paper, we study the dynamics of soiltransmitted helminth infection. We formulate and analyse a deterministic compartmental model using nonlinear differential equations. The basic reproduction number is obtained and both diseasefree and endemic equilibrium points are shown to be asymptotically stable under given threshold conditions. The model may exhibit backward bifurcation for some parameter

A Comparative Analysis of Visual Encoding Models Based on Classification and Segmentation TaskDriven CNNs Comput. Math. Method Med. (IF 1.77) Pub Date : 20200801
Ziya Yu; Chi Zhang; Linyuan Wang; Li Tong; Bin YanNowadays, visual encoding models use convolution neural networks (CNNs) with outstanding performance in computer vision to simulate the process of human information processing. However, the prediction performances of encoding models will have differences based on different networks driven by different tasks. Here, the impact of network tasks on encoding models is studied. Using functional magnetic

Does Determination of Initial Cluster Centroids Improve the Performance of Means Clustering Algorithm? Comparison of Three Hybrid Methods by Genetic Algorithm, Minimum Spanning Tree, and Hierarchical Clustering in an Applied Study Comput. Math. Method Med. (IF 1.77) Pub Date : 20200801
Saeedeh Pourahmad; Atefeh Basirat; Amir Rahimi; Marziyeh DoostfatemehRandom selection of initial centroids (centers) for clusters is a fundamental defect in means clustering algorithm as the algorithm’s performance depends on initial centroids and may end up in local optimizations. Various hybrid methods have been introduced to resolve this defect in means clustering algorithm. As regards, there are no comparative studies comparing these methods in various aspects

A Simple Method to Train the AI Diagnosis Model of Pulmonary Nodules Comput. Math. Method Med. (IF 1.77) Pub Date : 20200801
Zhehao He; Wang Lv; Jian HuBackground. The differential diagnosis of subcentimetre lung nodules with a diameter of less than 1 cm has always been one of the problems of imaging doctors and thoracic surgeons. We plan to create a deep learning model for the diagnosis of pulmonary nodules in a simple method. Methods. Image data and pathological diagnosis of patients come from the First Affiliated Hospital of Zhejiang University

A Further Study on Multiperiod Health Diagnostics Methodology under a SingleValued Neutrosophic Set Comput. Math. Method Med. (IF 1.77) Pub Date : 20200801
Jason Chihsheng Chou; YiFong Lin; Scott ShuCheng LinEmploying the concept and function of tangency with similarity measures and counterpart distances for reliable medical consultations has been extensively studied in the past decades and results in lots of isomorphic measures for application. We compared the majority of such isomorphic measures proposed by various researchers and classified them into (a) maximum norm and (b) onenorm categories. Moreover

Research and Verification of Convolutional Neural Network Lightweight in BCI Comput. Math. Method Med. (IF 1.77) Pub Date : 20200801
Shipu Xu; Runlong Li; Yunsheng Wang; Yong Liu; Wenwen Hu; Yingjing Wu; Chenxi Zhang; Chang Liu; Chao MaWith the increasing of depth and complexity of the convolutional neural network, parameter dimensionality and volume of computing have greatly restricted its applications. Based on the SqueezeNet network structure, this study introduces a block convolution and uses channel shuffle between blocks to alleviate the information jam. The method is aimed at reducing the dimensionality of parameters of in

An Inverse Problem Solution Scheme for Solving the Optimization Problem of DrugControlled Release from Multilaminated Devices Comput. Math. Method Med. (IF 1.77) Pub Date : 20200801
Xinming ZhangThe optimization problem of drug release based on the multilaminated drugcontrolled release devices has been solved in this paper under the inverse problem solution scheme. From the viewpoint of inverse problem, the solution of optimization problem can be regarded as the solution problem of a Fredholm integral equation of first kind. The solution of the Fredholm integral equation of first kind is

An Epilepsy Detection Method Using Multiview Clustering Algorithm and Deep Features Comput. Math. Method Med. (IF 1.77) Pub Date : 20200801
Qianyi Zhan; Wei HuThe automatic detection of epilepsy is essentially the classification of EEG signals of seizures and nonseizures, and its purpose is to distinguish the different characteristics of seizure brain electrical signals and normal brain electrical signals. In order to improve the effect of automatic detection, this study proposes a new classification method based on unsupervised multiview clustering results

Research of Epidemic Big Data Based on Improved Deep Convolutional Neural Network Comput. Math. Method Med. (IF 1.77) Pub Date : 20200722
Wendong WangIn recent years, with the acceleration of the aging process and the aggravation of life pressure, the proportion of chronic epidemics has gradually increased. A large amount of medical data will be generated during the hospitalization of diabetics. It will have important practical significance and social value to discover potential medical laws and valuable information among medical data. In view of

SpatialFrequency Feature Learning and Classification of Motor Imagery EEG Based on Deep Convolution Neural Network Comput. Math. Method Med. (IF 1.77) Pub Date : 20200720
Minmin Miao; Wenjun Hu; Hongwei Yin; Ke ZhangEEG pattern recognition is an important part of motor imagery (MI) based brain computer interface (BCI) system. Traditional EEG pattern recognition algorithm usually includes two steps, namely, feature extraction and feature classification. In feature extraction, common spatial pattern (CSP) is one of the most frequently used algorithms. However, in order to extract the optimal CSP features, prior

Comparison of Common Methods for Precision Volume Measurement of Hematoma Comput. Math. Method Med. (IF 1.77) Pub Date : 20200717
Minhong Chen; Zhong Li; Jianping Ding; Xingqi Lu; Yinan Cheng; Jiayun LinPurpose. Our aim is to conduct analysis and comparison of some methods commonly used to measure the volume of hematoma, for example, slice method, voxelization method, and 3DSlicer software method (projection method). Method. In order to validate the accuracy of the slice method, voxelization method, and 3DSlicer method, these three methods were first applied to measure two known volumetric models

An Approach to the Computation of the Euler Number by means of the Vertex Chain Code Comput. Math. Method Med. (IF 1.77) Pub Date : 20200716
Ernesto Bribiesca; UlfDietrich Braumann; Angel CarrilloBermejo; Humberto SossaAzuelaWe present an approach to compute the number of holes in binary images using the Vertex Chain Code (VCC); the VCC was developed for representing and analyzing 2D shapes composed of cells. Using this code, it is possible to relate the outer to inner vertices of any 2D shape and to find interesting properties. Now, in this paper, we describe more properties of the VCC, such as the computation of the

An Intelligent Diagnosis Method of Brain MRI Tumor Segmentation Using Deep Convolutional Neural Network and SVM Algorithm Comput. Math. Method Med. (IF 1.77) Pub Date : 20200714
Wentao Wu; Daning Li; Jiaoyang Du; Xiangyu Gao; Wen Gu; Fanfan Zhao; Xiaojie Feng; Hong YanAmong the currently proposed brain segmentation methods, brain tumor segmentation methods based on traditional image processing and machine learning are not ideal enough. Therefore, deep learningbased brain segmentation methods are widely used. In the brain tumor segmentation method based on deep learning, the convolutional network model has a good brain segmentation effect. The deep convolutional

Assessing the Impact of Optimal Health Education Programs on the Control of Zoonotic Diseases Comput. Math. Method Med. (IF 1.77) Pub Date : 20200711
A. MhlangaTo better understand the dynamics of zoonotic diseases, we propose a deterministic mathematical model to study the dynamics of zoonotic brucellosis with a focus on developing countries. The model contains all the relevant biological details, including indirect transmission by the environment. We analyze the essential dynamic behavior of the model and perform an optimal control study to design effective

Nonstationary Model of Oxygen Transport in Brain Tissue Comput. Math. Method Med. (IF 1.77) Pub Date : 20200711
Andrey E. Kovtanyuk; Alexander Yu. Chebotarev; Nikolai D. Botkin; Varvara L. Turova; Irina N. Sidorenko; Renée LampeThe paper addresses the mathematical study of a nonstationary continuum model describing oxygen propagation in cerebral substance. The model allows to estimate the rate of oxygen saturation and stabilization of oxygen concentration in relatively large parts of cerebral tissue. A theoretical and numerical analysis of the model is performed. The unique solvability of the underlying initialboundary value

Finite Element Analysis of the Mechanism of Traumatic Aortic Rupture (TAR) Comput. Math. Method Med. (IF 1.77) Pub Date : 20200707
JiFeng Nan; Mohammadreza Rezaei; Rashid Mazhar; Fadi Jaber; Farayi Musharavati; Erfan Zalnezhad; Muhammad E. H. ChowdhuryAs many as 80% of patients with TAR die on the spot while out of those reaching a hospital, 30% would die within 24 hours. Thus, it is essential to better understand and prevent this injury. The exact mechanics of TAR are unknown. Although most researchers approve it as a commonsense deceleration injury, the exact detailed mechanism of TRA still remains unidentified. In this work, a deceleration mechanism

Weighed Gene Coexpression Network Analysis Screens the Potential Long Noncoding RNAs and Genes Associated with Progression of Coronary Artery Disease Comput. Math. Method Med. (IF 1.77) Pub Date : 20200706
Lang Wang; Jun Hu; Jiali Zhou; Fan Guo; Tan Yao; Liang ZhangBackground. Coronary artery disease (CAD) is a type of heart disease with a high morbidity rate. This study is aimed at identifying potential biomarkers closely related to the progression of CAD. Materials and Methods. A microarray dataset of GSE59867 was downloaded from a public database, Gene Expression Omnibus, which included 46 cases of stable CAD without a history of myocardial infarction (MI)

Holistic View on Cell Survival and DNA Damage: How ModelBased Data Analysis Supports Exploration of Dynamics in Biological Systems Comput. Math. Method Med. (IF 1.77) Pub Date : 20200706
Mathias S. Weyland; Pauline ThumserHenner; Katarzyna J. Nytko; Carla Rohrer Bley; Simone Ulzega; Alke PetriFink; Marco Lattuada; Rudolf M. Füchslin; Stephan ScheideggerIn this work, a method is established to calibrate a model that describes the basic dynamics of DNA damage and repair. The model can be used to extend planning for radiotherapy and hyperthermia in order to include the biological effects. In contrast to “syntactic” models (e.g., describing molecular kinetics), the model used here describes radiobiological semantics, resulting in a more powerful model

Multimodal MRI Brain Tumor Image Segmentation Using Sparse Subspace Clustering Algorithm Comput. Math. Method Med. (IF 1.77) Pub Date : 20200704
Li Liu; Liang Kuang; Yunfeng JiBrain tumors are one of the most deadly diseases with a high mortality rate. The shape and size of the tumor are random during the growth process. Brain tumor segmentation is a brain tumor assisted diagnosis technology that separates different brain tumor structures such as edema and active and tumor necrosis tissues from normal brain tissue. Magnetic resonance imaging (MRI) technology has the advantages

Bayesian Multilevel Analysis of Utilization of Antenatal Care Services in Ethiopia Comput. Math. Method Med. (IF 1.77) Pub Date : 20200704
Cheru Atsmegiorgis Kitabo; Ehit Tesfu DamtieIn subSaharan Africa, 72% of pregnant women received an antenatal care visit at least once in their pregnancy period. Ethiopia has one of the highest rates of maternal mortality in subSaharan African countries. So, this high maternal mortality levels remain a major public health problem. According to EDHS, 2016, the antenatal care (ANC), delivery care (DC), and postnatal care (PNC) were 62%, 73%

CTTEE Image Registration for Surgical Navigation of Congenital Heart Disease Based on a Cycle Adversarial Network Comput. Math. Method Med. (IF 1.77) Pub Date : 20200702
Yunfei Lu; Bing Li; Ningtao Liu; JiaWei Chen; Li Xiao; Shuiping Gou; Linlin Chen; Meiping Huang; Jian ZhuangTransesophageal echocardiography (TEE) has become an essential tool in interventional cardiologist’s daily toolbox which allows a continuous visualization of the movement of the visceral organ without trauma and the observation of the heartbeat in real time, due to the sensor’s location at the esophagus directly behind the heart and it becomes useful for navigation during the surgery. However, TEE

Applying Queuing Theory and Mixed Integer Programming to Blood Center Nursing Schedules of a Large Hospital in China Comput. Math. Method Med. (IF 1.77) Pub Date : 20200701
Li Luo; Xiaofei Liu; Xinyuan Cui; Yuanjun Cheng; Xinzhu Yu; Yue Li; Li Jiang; Mingying TanBlood centers in large hospitals in China are facing serious problems, including complex patient queues and inflexible nursing schedules. This study is aimed at developing a flexible scheduling method for blood center nurses. By systematically analyzing the constraints that affect scheduling, a flexible scheduling model is established based on queuing theory and mixed integer programming. This combined

Factors Influencing Information Service Quality of China Hospital: The Case Study of since 2017 of a Hospital Information Platform in China Comput. Math. Method Med. (IF 1.77) Pub Date : 20200701
Lei Jiao; HuaPing Xiao; XiaoZhuo Zhu; Xu ZhaoBackground: As a country with the largest number of netizens around the world, China enjoys improving social information services based on the Internet. With such a large quantity of network users, it is inevitable for China’s hospitals at various levels to provide patients and the public with information services by setting up their own official websites. But it is still elusive for the factors affecting

Comparison of Variable Selection Methods for TimetoEvent Data in HighDimensional Settings Comput. Math. Method Med. (IF 1.77) Pub Date : 20200701
Julia Gilhodes; Florence Dalenc; Jocelyn Gal; Christophe Zemmour; Eve Leconte; JeanMarie Boher; Thomas FilleronOver the last decades, molecular signatures have become increasingly important in oncology and are opening up a new area of personalized medicine. Nevertheless, biological relevance and statistical tools necessary for the development of these signatures have been called into question in the literature. Here, we investigate six typical selection methods for highdimensional settings and survival endpoints

Systematic Identification of lncRNAAssociated ceRNA Networks in Immune Thrombocytopenia Comput. Math. Method Med. (IF 1.77) Pub Date : 20200630
Zhenwei Fan; Xuan Wang; Peng Li; Chunli Mei; Min Zhang; Chunshan Zhao; Yan SongPrimary immune thrombocytopenia (ITP) is an autoimmune disease. However, the molecular mechanisms underlying ITP remained to be further investigated. In the present study, we analyzed a series of public datasets (including GSE43177 and GSE43178) and identified 468 upregulated mRNAs, 272 downregulated mRNAs, 134 upregulated lncRNAs, 23 downregulated lncRNAs, 29 upregulated miRNAs, and 39 downregulated

An Indirect Multimodal Image Registration and Completion Method Guided by Image Synthesis Comput. Math. Method Med. (IF 1.77) Pub Date : 20200630
Huan Yang; Pengjiang Qian; Chao FanMultimodal registration is a challenging task due to the significant variations exhibited from images of different modalities. CT and MRI are two of the most commonly used medical images in clinical diagnosis, since MRI with multicontrast images, together with CT, can provide complementary auxiliary information. The deformable image registration between MRI and CT is essential to analyze the relationships

miR215 Inhibits Colorectal Cancer Cell Migration and Invasion via Targeting StearoylCoA Desaturase Comput. Math. Method Med. (IF 1.77) Pub Date : 20200630
Xinhua Xu; Yan Ding; Jun Yao; Zhiping Wei; Haipeng Jin; Chen Chen; Jun Feng; Rongbiao YingBackground. This study was aimed at exploring the effects of miR215 and its target gene stearoylCoA desaturase (SCD) on colorectal cancer (CRC) cell migration and invasion. Methods. Here, we analyzed the relationship between miR215 and SCD, as well as the regulation of miR215 on CRC cells. We constructed wildtype and mutant plasmids of SCD to identify whether SCD was a target gene of miR215 by

Comparison of COVID19 Pandemic Dynamics in Asian Countries with Statistical Modeling Comput. Math. Method Med. (IF 1.77) Pub Date : 20200628
Min Zuo; Saima K. Khosa; Zubair Ahmad; Zahra AlmaspoorIn the current scenario, the outbreak of a pandemic disease COVID19 is of great interest. A broad statistical analysis of this event is still to come, but it is immediately needed to evaluate the disease dynamics in order to arrange the appropriate quarantine activities, to estimate the required number of places in hospitals, the level of individual protection, the rate of isolation of infected persons

Attention Optimization Method for EEG via the TGAM Comput. Math. Method Med. (IF 1.77) Pub Date : 20200618
Yu Wu; Ning XieSince the 21st century, noninvasive braincomputer interface (BCI) has developed rapidly, and braincomputer devices have gradually moved from the laboratory to the mass market. Among them, the TGAM (ThinkGear Asic Module) and its encapsulate algorithm have been adopted by many research teams and faculty members around the world. However, due to the limited development cost, the effectiveness of the

Prediction of HighRisk Types of Human Papillomaviruses Using Reduced Amino Acid Modes Comput. Math. Method Med. (IF 1.77) Pub Date : 20200618
Xinnan Xu; Rui Kong; Xiaoqing Liu; Pingan He; Qi DaiA human papillomavirus type plays an important role in the early diagnosis of cervical cancer. Most of the prediction methods use protein sequence and structure information, but the reduced amino acid modes have not been used until now. In this paper, we introduced the modes of reduced amino acids to predict highrisk HPV. We first reduced 20 amino acids into several nonoverlapping groups and calculated

An Automated Workflow for Hemodynamic Computations in Cerebral Aneurysms Comput. Math. Method Med. (IF 1.77) Pub Date : 20200617
CosminIoan Nita; Takashi Suzuki; Lucian Mihai Itu; Viorel Mihalef; Hiroyuki Takao; Yuichi Murayama; Puneet Sharma; Thomas Redel; Saikiran RapakaIn recent years, computational fluid dynamics (CFD) has become a valuable tool for investigating hemodynamics in cerebral aneurysms. CFD provides flowrelated quantities, which have been shown to have a potential impact on aneurysm growth and risk of rupture. However, the adoption of CFD tools in clinical settings is currently limited by the high computational cost and the engineering expertise required

Detection of Solitary Pulmonary Nodules Based on BrainComputer Interface Comput. Math. Method Med. (IF 1.77) Pub Date : 20200615
Shi Qiu; Junjun Li; Mengdi Cong; Chun Wu; Yan Qin; Ting LiangSolitary pulmonary nodules are the main manifestation of pulmonary lesions. Doctors often make diagnosis by observing the lung CT images. In order to further study the brain response structure and construct a braincomputer interface, we propose an isolated pulmonary nodule detection model based on a braincomputer interface. First, a single channel timefrequency feature extraction model is constructed

Construction and Comprehensive Analysis of Dysregulated Long Noncoding RNAAssociated Competing Endogenous RNA Network in Moyamoya Disease Comput. Math. Method Med. (IF 1.77) Pub Date : 20200613
Xuefeng Gu; Dongyang Jiang; Yue Yang; Peng Zhang; Guoqing Wan; Wangxian Gu; Junfeng Shi; Liying Jiang; Bing Chen; Yanjun Zheng; Dingsheng Liu; Sufen Guo; Changlian LuBackground. Moyamoya disease (MMD) is a rare cerebrovascular disease characterized by chronic progressive stenosis or occlusion of the bilateral internal carotid artery (ICA), the anterior cerebral artery (ACA), and the middle cerebral artery (MCA). MMD is secondary to the formation of an abnormal vascular network at the base of the skull. However, the etiology and pathogenesis of MMD remain poorly

Electrical Impedance TomographyBased Abdominal Subcutaneous Fat Estimation Method Using Deep Learning Comput. Math. Method Med. (IF 1.77) Pub Date : 20200611
Kyounghun Lee; Minha Yoo; Ariungerel Jargal; Hyeuknam KwonThis paper proposes a deep learning method based on electrical impedance tomography (EIT) to estimate the thickness of abdominal subcutaneous fat. EIT for evaluating the thickness of abdominal subcutaneous fat is an absolute imaging problem that aims at reconstructing conductivity distributions from currenttovoltage data. Existing reconstruction methods based on EIT have difficulty handling the inherent

The EEGBased Attention Analysis in Multimedia mLearning Comput. Math. Method Med. (IF 1.77) Pub Date : 20200610
Dan Ni; Shuo Wang; Guocheng LiuIn recent years, research on braincomputer interfaces has been increasing in the field of education, and mobile learning has become a very important way of learning. In this study, EEG experiment of a group of iPadbased mobile learners was conducted through algorithm optimization on the TGAM chip. Under the three learning media (text, text + graphic, and video), the researchers analyzed the difference

A Game TheoryBased Model for Predicting Depression due to Frustration in Competitive Environments. Comput. Math. Method Med. (IF 1.77) Pub Date : 20200603
R Loula,L H A MonteiroA computational model based on game theory is here proposed to forecast the prevalence of depression caused by frustration in a competitive environment. This model comprises a spatially structured game, in which the individuals are socially connected. This game, which is equivalent to the wellknown prisoner’s dilemma, represents the payoffs that can be received by the individuals in the labor market

A Global Inhomogeneous Intensity Clustering (GINC) Based Active Contour Model for Image Segmentation and Bias Correction. Comput. Math. Method Med. (IF 1.77) Pub Date : 20200601
Chaolu Feng,Jinzhu Yang,Chunhui Lou,Wei Li,Kun Yu,Dazhe ZhaoImage segmentation is still an open problem especially when intensities of the objects of interest are overlapped due to the presence of intensity inhomogeneities. A bias correction embedded level set model is proposed in this paper where inhomogeneities are estimated by orthogonal primary functions. First, an inhomogeneous intensity clustering energy is defined based on global distribution characteristics

A Novel 3D Reconstruction Algorithm of MotionBlurred CT Image. Comput. Math. Method Med. (IF 1.77) Pub Date : 20200601
Zhang Jing,Guo Qiang,Han Fang,Li ZhanLi,Li HongAn,Sun YuThe majority of medical workers are eager to obtain realistic and realtime CT 3D reconstruction results. However, autonomous or involuntary motion of patients can cause blurring of CT images. For the 3D reconstruction scene of motionblurred CT image, this paper consists of two parts: firstly, a GAN image translation network deblurring algorithm is proposed to remove blurred results. This algorithm

Influences of Daily Life Habits on Risk Factors of Stroke Based on Decision Tree and Correlation Matrix. Comput. Math. Method Med. (IF 1.77) Pub Date : 20200601
Zeguo Shao,Yuhong Xiang,Yingchao Zhu,Aiqin Fan,Peng ZhangPurpose. To explore the influences of smoking, alcohol consumption, drinking tea, diet, sleep, and exercise on the risk of stroke and relationships among the factors, present corresponding knowledgebased rules, and provide a scientific basis for assessment and intervention of risk factors of stroke. Methods. The decision tree C4.5 algorithm was optimized and utilized to establish a model for stroke

Improved KaplanMeier Estimator in Survival Analysis Based on Partially RankOrdered Set Samples Comput. Math. Method Med. (IF 1.77) Pub Date : 20200531
Samane Nematolahi; Sahar Nazari; Zahra Shayan; Seyyed Mohammad Taghi Ayatollahi; Ali AmanatiThis study presents a novel methodology to investigate the nonparametric estimation of a survival probability under random censoring time using the ranked observations from a Partially RankOrdered Set (PROS) sampling design and employs it in a hematological disorder study. The PROS sampling design has numerous applications in medicine, social sciences and ecology where the exact measurement of the

Modeling the Influence of Nonclinic Visits on the Transmission of Respiratory Diseases. Comput. Math. Method Med. (IF 1.77) Pub Date : 20200531
Yunting Bao,Yanlong Xu,Longxing Qi,Sulan ZhaiAccording to the information reflected by Anhui Center for Disease Control (Anhui CDC) in Hefei, Anhui province of China, some patients infected with respiratory diseases did not seek medical treatment (nonclinic visits) due to their strong resistance, and the influence of them on the spread of respiratory diseases has not been known. A SIS model with considering the nonclinic visits was established;

A Lead Field TwoDomain Model for Longitudinal Neural TractsAnalytical Framework and Implications for Signal Bandwidth. Comput. Math. Method Med. (IF 1.77) Pub Date : 20200529
G Fischer,M Kofler,M Handler,D BaumgartenSomatosensory evoked potentials are a wellestablished tool for assessing volley conduction in afferent neural pathways. However, from a clinical perspective, recording of spinal signals is still a demanding task due to the low amplitudes compared to relevant noise sources. Computer modeling is a powerful tool for gaining insight into signal genesis and, thus, for promoting future innovations in signal

Modeling the Spread of COVID19 Infection Using a Multilayer Perceptron. Comput. Math. Method Med. (IF 1.77) Pub Date : 20200529
Zlatan Car,Sandi Baressi Šegota,Nikola Anđelić,Ivan Lorencin,Vedran MrzljakCoronavirus (COVID19) is a highly infectious disease that has captured the attention of the worldwide public. Modeling of such diseases can be extremely important in the prediction of their impact. While classic, statistical, modeling can provide satisfactory models, it can also fail to comprehend the intricacies contained within the data. In this paper, authors use a publicly available dataset, containing

Identifying Methamphetamine Dependence Using Regional Homogeneity in BOLD Signals Comput. Math. Method Med. (IF 1.77) Pub Date : 20200528
Hufei Yu; Shucai Huang; Xiaojie Zhang; Qiuping Huang; Jun Liu; Hongxian Chen; Yan TangMethamphetamine is a highly addictive drug of abuse, which will cause a series of abnormal consequences mentally and physically. This paper is aimed at studying whether the abnormalities of regional homogeneity (ReHo) could be effective features to distinguish individuals with methamphetamine dependence (MAD) from control subjects using machinelearning methods. We made use of restingstate fMRI to

A Parallel Algorithm Framework for Feature Extraction of EEG Signals on MPI Comput. Math. Method Med. (IF 1.77) Pub Date : 20200527
Qi Xiong; Xinman Zhang; WenFeng Wang; Yuhong GuIn this paper, we present a parallel framework based on MPI for a large dataset to extract power spectrum features of EEG signals so as to improve the speed of brain signal processing. At present, the Welch method has been wildly used to estimate the power spectrum. However, the traditional Welch method takes a lot of time especially for the large dataset. In view of this, we added the MPI into the

CUL1Mediated Organelle Fission Pathway Inhibits the Development of Chronic Obstructive Pulmonary Disease. Comput. Math. Method Med. (IF 1.77) Pub Date : 20200526
Ran Li,Feng Xu,Xiao Wu,Shaoping Ji,Ruixue XiaChronic obstructive pulmonary disease (COPD) is a global highincidence chronic airway inflammation disease. Its deterioration will lead to more serious lung lesions and even lung cancer. Therefore, it is urgent to determine the pathogenesis of COPD and find potential therapeutic targets. The purpose of this study is to reveal the molecular mechanism of COPD disease development through indepth analysis

A New ExtendedX Family of Distributions: Properties and Applications. Comput. Math. Method Med. (IF 1.77) Pub Date : 20200526
Mi Zichuan,Saddam Hussain,Anum Iftikhar,Muhammad Ilyas,Zubair Ahmad,Dost Muhammad Khan,Sadaf ManzoorDuring the past couple of years, statistical distributions have been widely used in applied areas such as reliability engineering, medical, and financial sciences. In this context, we come across a diverse range of statistical distributions for modeling heavy tailed data sets. Wellknown distributions are lognormal, log, various versions of Pareto, loglogistic, Weibull, gamma, exponential, Rayleigh

HighThroughput Docking and Molecular Dynamics Simulations towards the Identification of Potential Inhibitors against Human Coagulation Factor XIIa. Comput. Math. Method Med. (IF 1.77) Pub Date : 20200522
Dongfang Xu,Guangpu Xue,Bangya Peng,Zanjie Feng,Hongling Lu,Lihu GongHuman coagulation factor XIIa (FXIIa) is a trypsinlike serine protease that is involved in pathologic thrombosis. As a potential target for designing safe anticoagulants, FXIIa has received a great deal of interest in recent years. In the present study, we employed virtual highthroughput screening of 500,064 compounds within Enamine database to acquire the most potential inhibitors of FXIIa. Subsequently

Interpretable Learning Approaches in RestingState Functional Connectivity Analysis: The Case of Autism Spectrum Disorder. Comput. Math. Method Med. (IF 1.77) Pub Date : 20200518
Jinlong Hu,Lijie Cao,Tenghui Li,Bin Liao,Shoubin Dong,Ping LiDeep neural networks have recently been applied to the study of brain disorders such as autism spectrum disorder (ASD) with great success. However, the internal logics of these networks are difficult to interpret, especially with regard to how specific network architecture decisions are made. In this paper, we study an interpretable neural network model as a method to identify ASD participants from

Auxiliary Medical Decision System for Prostate Cancer Based on Ensemble Method. Comput. Math. Method Med. (IF 1.77) Pub Date : 20200518
Jia Wu,Qinghe Zhuang,Yanlin TanProstate cancer (PCa) is one of the main diseases that endanger men’s health worldwide. In developing countries, due to the large number of patients and the lack of medical resources, there is a big conflict between doctors and patients. To solve this problem, an auxiliary medical decision system for prostate cancer was constructed. The system used six relevant tumor markers as the input features and

EEG Signal and Feature Interaction ModelingBased Eye Behavior Prediction Research. Comput. Math. Method Med. (IF 1.77) Pub Date : 20200516
Pengcheng Ma,Qian GaoIn recent years, with the development of brain science and biomedical engineering, as well as the rapid development of electroencephalogram (EEG) signal analysis methods, using EEG signals to monitor human health has become a very popular research field. The innovation of this paper is to analyze the EEG signal for the first time by building a depth factorization machine model, so that on the basis

Association between Timing of Surgical Intervention and Mortality in 15,813 Acute Pancreatitis. Comput. Math. Method Med. (IF 1.77) Pub Date : 20200516
Lan Lan,Jiawei Luo,Xiaoyan Yang,Dujiang Yang,Mengjiao Li,Fangwei Chen,Nianyin Zeng,Xiaobo ZhouObjective. In order to find the quantitative relationship between timing of surgical intervention and risk of death in necrotizing pancreatitis. Methods. The generalized additive model was applied to quantitate the relationship between surgical time (from the onset of acute pancreatitis to first surgical intervention) and risk of death adjusted for demographic characteristics, infection, organ failure

Development and Application of One SeparationFree Safety Tube on the Disposable Infusion Needle. Comput. Math. Method Med. (IF 1.77) Pub Date : 20200516
Weifen Lu,Qianli Pan,Yinxin Zhou,Wenyu Chen,Hongyan Zhang,Weibo QiObjective. To develop a new type infusion set and apply it to the clinic, as well as explore its effectiveness in the prevention from needle stick injuries. Methods. A total of 200 inpatients who were in need of intravenous infusion with a disposable infusion needle were included and randomly divided into two groups: intervention group and control group. Disposable infusion needles with a separationfree

Multichart Schemes for Detecting Changes in Disease Incidence. Comput. Math. Method Med. (IF 1.77) Pub Date : 20200515
Gideon Mensah Engmann,Dong HanSeveral methods have been proposed in open literatures for detecting changes in disease outbreak or incidence. Most of these methods are likelihoodbased as well as the direct application of Shewhart, CUSUM and EWMA schemes. We use CUSUM, EWMA and EWMACUSUM multichart schemes to detect changes in disease incidence. Multichart is a combination of several single charts that detects changes in a process

Construction and Analysis of Double Helix for Triangular Bipyramid and Pentangular Bipyramid. Comput. Math. Method Med. (IF 1.77) Pub Date : 20200514
Tao DengDNA cages can be joined together to make larger 3D nanostructures on which molecular electronic circuits and tiny containers are built for drug delivery. The mathematical models for these promising nanomaterials play important roles in clarifying their assembly mechanism and understanding their structures. In this study, we propose a mathematical and computer method to construct permissible topological

Prediction of Drug Side Effects with a Refined Negative Sample Selection Strategy. Comput. Math. Method Med. (IF 1.77) Pub Date : 20200509
Haiyan Liang,Lei Chen,Xian Zhao,Xiaolin ZhangDrugs are an important way to treat various diseases. However, they inevitably produce side effects, bringing great risks to human bodies and pharmaceutical companies. How to predict the side effects of drugs has become one of the essential problems in drug research. Designing efficient computational methods is an alternative way. Some studies paired the drug and side effect as a sample, thereby modeling

CrossSubject Seizure Detection in EEGs Using Deep Transfer Learning. Comput. Math. Method Med. (IF 1.77) Pub Date : 20200508
Baocan Zhang,Wennan Wang,Yutian Xiao,Shixiao Xiao,Shuaichen Chen,Sirui Chen,Gaowei Xu,Wenliang CheElectroencephalography (EEG) plays an import role in monitoring the brain activities of patients with epilepsy and has been extensively used to diagnose epilepsy. Clinically reading tens or even hundreds of hours of EEG recordings is very time consuming. Therefore, automatic detection of seizure is of great importance. But the huge diversity of EEG signals belonging to different patients makes the