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ReferenceDriven Undersampled MR Image Reconstruction Using Wavelet SparsityConstrained Deep Image Prior Comput. Math. Method Med. (IF 1.77) Pub Date : 20210122
Di Zhao; Yanhu Huang; Feng Zhao; Binyi Qin; Jincun ZhengDeep learning has shown potential in significantly improving performance for undersampled magnetic resonance (MR) image reconstruction. However, one challenge for the application of deep learning to clinical scenarios is the requirement of large, highquality patientbased datasets for network training. In this paper, we propose a novel deep learningbased method for undersampled MR image reconstruction

Choroid Segmentation of Retinal OCT Images Based on CNN Classifier and  Fitter Comput. Math. Method Med. (IF 1.77) Pub Date : 20210116
Fang He; Rachel Ka Man Chun; Zicheng Qiu; Shijie Yu; Yun Shi; Chi Ho To; Xiaojun ChenOptical coherence tomography (OCT) is a noninvasive crosssectional imaging technology used to examine the retinal structure and pathology of the eye. Evaluating the thickness of the choroid using OCT images is of great interests for clinicians and researchers to monitor the choroidal thickness in many ocular diseases for diagnosis and management. However, manual segmentation and thickness profiling

Screening of Prospective Plant Compounds as H1R and CL1R Inhibitors and Its Antiallergic Efficacy through Molecular Docking Approach Comput. Math. Method Med. (IF 1.77) Pub Date : 20210112
Hasan Zulfiqar; Muhammad Shareef Masoud; Hui Yang; ShuGuang Han; ChengYan Wu; Hao LinAllergens have the ability to enter the body and cause illness. Leukotriene is the widespread allergen which could stimulate mast cells to discharge histamine which causes allergy symptoms. An effective strategy for treating leukotrieneinduced allergy is to find the inhibitors of leukotriene or histamine activity from phytochemicals. For this purpose, a library of 8,500 phytochemicals was generated

Analyzing Surgical Treatment of Intestinal Obstruction in Children with Artificial Intelligence Comput. Math. Method Med. (IF 1.77) Pub Date : 20210111
WangRen Qiu; Gang Chen; Jin Wu; Jun Lei; Lei Xu; ShouHua ZhangIntestinal obstruction is a common surgical emergency in children. However, it is challenging to seek appropriate treatment for childhood ileus since many diagnostic measures suitable for adults are not applicable to children. The rapid development of machine learning has spurred much interest in its application to medical imaging problems but little in medical text mining. In this paper, a twolayer

iBLP: An XGBoostBased Predictor for Identifying Bioluminescent Proteins Comput. Math. Method Med. (IF 1.77) Pub Date : 20210107
Dan Zhang; HuaDong Chen; Hasan Zulfiqar; ShiShi Yuan; QinLai Huang; ZhaoYue Zhang; KeJun DengBioluminescent proteins (BLPs) are a class of proteins that widely distributed in many living organisms with various mechanisms of light emission including bioluminescence and chemiluminescence from luminous organisms. Bioluminescence has been commonly used in various analytical research methods of cellular processes, such as gene expression analysis, drug discovery, cellular imaging, and toxicity

iT3SEPX: Identification of Bacterial Type III Secreted Effectors Using PSSM Profiles and XGBoost Feature Selection Comput. Math. Method Med. (IF 1.77) Pub Date : 20210106
Chenchen Ding; Haitao Han; Qianyue Li; Xiaoxia Yang; Taigang LiuIdentification of bacterial type III secreted effectors (T3SEs) has become a popular research topic in the field of bioinformatics due to its crucial role in understanding hostpathogen interaction and developing better therapeutic targets against the pathogens. However, the recognition of all effector proteins by using traditional experimental approaches is often timeconsuming and laborious. Therefore

iMPTCEHnetwork: A Multilabel Classifier for Identifying Metabolic Pathway Types of Chemicals and Enzymes with a Heterogeneous Network Comput. Math. Method Med. (IF 1.77) Pub Date : 20210105
Yuanyuan Zhu; Bin Hu; Lei Chen; Qi DaiMetabolic pathway is an important type of biological pathways. It produces essential molecules and energies to maintain the life of living organisms. Each metabolic pathway consists of a chain of chemical reactions, which always need enzymes to participate in. Thus, chemicals and enzymes are two major components for each metabolic pathway. Although several metabolic pathways have been uncovered, the

iPTT(2 L)CNN: A TwoLayer Predictor for Identifying Promoters and Their Types in Plant Genomes by Convolutional Neural Network Comput. Math. Method Med. (IF 1.77) Pub Date : 20210105
Ang Sun; Xuan Xiao; Zhaochun XuA promoter is a short DNA sequence near to the start codon, responsible for initiating transcription of a specific gene in genome. The accurate recognition of promoters has great significance for a better understanding of the transcriptional regulation. Because of their importance in the process of biological transcriptional regulation, there is an urgent need to develop in silico tools to identify

Prognostic Correlation of an AutophagyRelated Gene Signature in Patients with Head and Neck Squamous Cell Carcinoma Comput. Math. Method Med. (IF 1.77) Pub Date : 20201229
Cai Yang; Hongxiang Mei; Liang Peng; Fulin Jiang; Bingjie Xie; Juan LiConsiderable evidence indicates that autophagy plays a vital role in the biological processes of various cancers. The aim of this study is to evaluate the prognostic value of autophagyrelated genes in patients with head and neck squamous cell carcinoma (HNSCC). Transcriptome expression profiles and clinical data acquired from The Cancer Genome Atlas (TCGA) database were analyzed by Cox proportional

Parameter Estimation and Prediction of COVID19 Epidemic Turning Point and Ending Time of a Case Study on SIR/SQAIR Epidemic Models Comput. Math. Method Med. (IF 1.77) Pub Date : 20201229
Amir Hossein Amiri Mehra; Mohsen Shafieirad; Zohreh Abbasi; Iman ZamaniIn this paper, the SIR epidemiological model for the COVID19 with unknown parameters is considered in the first strategy. Three curves (, , and ) are fitted to the real data of South Korea, based on a detailed analysis of the actual data of South Korea, taken from the Korea Disease Control and Prevention Agency (KDCA). Using the least square method and minimizing the error between the fitted curve

A Simple Cardiovascular Model for the Study of Hemorrhagic Shock Comput. Math. Method Med. (IF 1.77) Pub Date : 20201228
Luciano Curcio; Laura D’Orsi; Fabio Cibella; Linn WagnertAvraham; Dean Nachman; Andrea De GaetanoHemorrhagic shock is the number one cause of death on the battlefield and in civilian trauma as well. Mathematical modeling has been applied in this context for decades; however, the formulation of a satisfactory model that is both practical and effective has yet to be achieved. This paper introduces an upgraded version of the 2007 Zenker model for hemorrhagic shock termed the ZenCur model that allows

Prediction of the Dental Arch Perimeter in a Kurdish Sample in Sulaimani City Based on Other Linear Dental Arch Measurements as a Malocclusion Preventive Measure Comput. Math. Method Med. (IF 1.77) Pub Date : 20201222
Fadil Abdullah Kareem; Aras Maruf Rauf; Arass Jalal Noori; Trefa M. Ali MahmoodThe current study aimed to find a prediction equation to estimate the arch perimeter (AP) depending on various arch dimensions including intercanine width (ICW), intermolar width (IMW), interpremolar width (IPMW), and arch length (AL) in a sample of the Kurdish population in Sulaimani City. The study sample was 100 pairs of preorthodontic dental casts. Calculations of dental arch dimensions and perimeter

Measuring the Ocular Morphological Parameters of Guinea Pig Eye with Edge Detection and Curve Fitting Comput. Math. Method Med. (IF 1.77) Pub Date : 20201219
Yue Di; Ying Huang; Yajing Yang; XingTao Zhou; Wenting Luo; Haiyun Ye; Zhongbao Qiao; Na Lu; Tong QiaoAim. To identify the guinea pig eyeball with edge detection and curve fitting and devise a noncontact technology of measuring ocular morphological parameters of small experimental animal. Methods. Thirtynine eyeballs of guinea pig eyeballs were photographed to obtain the anterior and posterior surface; transverse and sagittal planes after the eyeballs were eviscerated. Next, the eyeball photos were

Task Transfer Learning for EEG Classification in Motor ImageryBased BCI System Comput. Math. Method Med. (IF 1.77) Pub Date : 20201215
Xuanci Zheng; Jie Li; Hongfei Ji; Lili Duan; Maozhen Li; Zilong Pang; Jie Zhuang; Lu Rongrong; Gao TianhaoThe motorimagery braincomputer interface system (MIBCI) has a board prospect for development. However, long calibration time and lack of enough MI commands limit its use in practice. In order to enlarge the command set, we add the combinations of traditional MI commands as new commands into the command set. We also design an algorithm based on transfer learning so as to decrease the calibration

EffectSize Estimation Using Semiparametric Hierarchical Mixture Models in DiseaseAssociation Studies with Neuroimaging Data Comput. Math. Method Med. (IF 1.77) Pub Date : 20201209
Ryo Emoto; Atsushi Kawaguchi; Kunihiko Takahashi; Shigeyuki MatsuiIn diseaseassociation studies using neuroimaging data, evaluating the biological or clinical significance of individual associations requires not only detection of diseaseassociated areas of the brain but also estimation of the magnitudes of the associations or effect sizes for individual brain areas. In this paper, we propose a modelbased framework for voxelbased inferences under spatial dependency

How to Determine the Early Warning Threshold Value of Meteorological Factors on Influenza through Big Data Analysis and Machine Learning Comput. Math. Method Med. (IF 1.77) Pub Date : 20201202
Hui Ge; Debao Fan; Ming Wan; Lizhu Jin; Xiaofeng Wang; Xuejie Du; Xu YangInfectious diseases are a major health challenge for the worldwide population. Since their rapid spread can cause great distress to the real world, in addition to taking appropriate measures to curb the spread of infectious diseases in the event of an outbreak, proper prediction and early warning before the outbreak of the threat of infectious diseases can provide an important basis for early and reasonable

Assessment of Three Mathematical Prediction Models for Forecasting the COVID19 Outbreak in Iran and Turkey Comput. Math. Method Med. (IF 1.77) Pub Date : 20201125
Majid Niazkar; Gökçen Eryılmaz Türkkan; Hamid Reza Niazkar; Yusuf Alptekin TürkkanCOVID19 pandemic has become a concern of every nation, and it is crucial to apply an estimation model with a favorablyhigh accuracy to provide an accurate perspective of the situation. In this study, three explicit mathematical prediction models were applied to forecast the COVID19 outbreak in Iran and Turkey. These models include a recursivebased method, Boltzmann Functionbased model and Beesham’s

Broad Learning Enhanced 1HMRS for Early Diagnosis of Neuropsychiatric Systemic Lupus Erythematosus Comput. Math. Method Med. (IF 1.77) Pub Date : 20201123
Yan Li; Zuhao Ge; Zhiyan Zhang; Zhiwei Shen; Yukai Wang; Teng Zhou; Renhua WuIn this paper, we explore the potential of using the multivoxel proton magnetic resonance spectroscopy (1HMRS) to diagnose neuropsychiatric systemic lupus erythematosus (NPSLE) with the assistance of a support vector machine broad learning system (BLSVM). We retrospectively analysed 23 confirmed patients and 16 healthy controls, who underwent a 3.0 T magnetic resonance imaging (MRI) sequence with

Challenges to the Application of Spatially Explicit Stochastic Simulation Models for FootandMouth Disease Control in Endemic Settings: A Systematic Review Comput. Math. Method Med. (IF 1.77) Pub Date : 20201121
Muhammad Usman Zaheer; Mo D. Salman; Kay K. Steneroden; Sheryl L. Magzamen; Stephen E. Weber; Shaun Case; Sangeeta RaoSimulation modeling has become common for estimating the spread of highly contagious animal diseases. Several models have been developed to mimic the spread of footandmouth disease (FMD) in specific regions or countries, conduct risk assessment, analyze outbreaks using historical data or hypothetical scenarios, assist in policy decisions during epidemics, formulate preparedness plans, and evaluate

PredAmylMLP: Prediction of Amyloid Proteins Using Multilayer Perceptron Comput. Math. Method Med. (IF 1.77) Pub Date : 20201121
Yanjuan Li; Zitong Zhang; Zhixia Teng; Xiaoyan LiuAmyloid is generally an aggregate of insoluble fibrin; its abnormal deposition is the pathogenic mechanism of various diseases, such as Alzheimer’s disease and type II diabetes. Therefore, accurately identifying amyloid is necessary to understand its role in pathology. We proposed a machine learningbased prediction model called PredAmylMLP, which consists of the following three steps: feature extraction

Modelling the Dynamics of Campylobacteriosis Using Nonstandard Finite Difference Approach with Optimal Control Comput. Math. Method Med. (IF 1.77) Pub Date : 20201119
Shaibu Osman; Houenafa Alain Togbenon; Dominic OtooCampylobacter genus is the bacteria responsible for campylobacteriosis infections, and it is the commonest cause of gastroenteritis in adults and infants. The disease is hyperendemic in children in most parts of developing countries. It is a zoonotic disease that can be contracted via direct contact, food, and water. In this paper, we formulated a deterministic model for Campylobacteriosis as a zoonotic

Potential Genes Associated with the Survival of Lung Adenocarcinoma Were Identified by Methylation Comput. Math. Method Med. (IF 1.77) Pub Date : 20201118
Ziyuan Shen; Chenlu He; Haimiao Chen; Lishun Xiao; Yingliang Jin; Shuiping HuangBackground. Lung adenocarcinoma (LUAD) is the most common pathological type of lung cancer. The purpose of this study is to search for genes related to the prognosis of LUAD through methylation based on a linear mixed model (LMM). Methods. Gene expression, methylation, and survival data of LUAD patients were downloaded from the TCGA database. Based on the LMM model, the GEMMA algorithm was used to

Modeling the Effects of Helminth Infection on the Transmission Dynamics of Mycobacterium tuberculosis under Optimal Control Strategies Comput. Math. Method Med. (IF 1.77) Pub Date : 20201118
Aristide G. Lambura; Gasper G. Mwanga; Livingstone Luboobi; Dmitry KuznetsovA deterministic mathematical model for the transmission and control of cointeraction of helminths and tuberculosis is presented, to examine the impact of helminth on tuberculosis and the effect of control strategies. The equilibrium point is established, and the effective reproduction number is computed. The diseasefree equilibrium point is confirmed to be asymptotically stable whenever the effective

Condition for Global Stability for a SEIR Model Incorporating Exogenous Reinfection and Primary Infection Mechanisms Comput. Math. Method Med. (IF 1.77) Pub Date : 20201118
Isaac Mwangi WangariA mathematical model incorporating exogenous reinfection and primary progression infection processes is proposed. Global stability is examined using the geometric approach which involves the generalization of PoincareBendixson criterion for systems of ordinary differential equations. Analytical results show that for a SusceptibleExposedInfectiveRecovered (SEIR) model incorporating exogenous reinfection

Risk Factors of Cerebral Infarction and Myocardial Infarction after Carotid Endarterectomy Analyzed by Machine Learning Comput. Math. Method Med. (IF 1.77) Pub Date : 20201116
Peng Bai; Yang Zhou; Yuan Liu; Gang Li; Zhengqian Li; Tao Wang; Xiangyang GuoObjective. The incidence of cerebral infarction and myocardial infarction is higher in patients with carotid endarterectomy (CEA). Based on the concept of coprotection of heart and brain, this study attempts to screen the related factors of early cerebral infarction and myocardial infarction after CEA with the method of machine learning to provide clinical data for the prevention of postoperative cerebral

Randomness for Nucleotide Sequences of SARSCoV2 and Its Related Subfamilies Comput. Math. Method Med. (IF 1.77) Pub Date : 20201116
RayMing ChenThe origin and evolution of SARSCoV2 has been an important issue in tackling COVID19. Research on these topics would enhance our knowledge of this virus and help us develop vaccines or predict its paths of mutations. There are many theoretical and clinical researches in this area. In this article, we devise a structural metric which directly measures the structural differences between any two nucleotide

Identification of Prognostic Biomarkers of Cutaneous Melanoma Based on Analysis of Tumor Mutation Burden Comput. Math. Method Med. (IF 1.77) Pub Date : 20201116
Jiaqiong Lin; Yan Lin; Zena Huang; Xiaoyong LiBackground. Immunotherapy offers a novel approach for the treatment of cutaneous melanoma, but the clinical efficiency varies for individual patients. In consideration of the high cost and adverse effects of immunotherapy, it is essential to explore the predictive biomarkers of outcomes. Recently, the tumor mutation burden (TMB) has been proposed as a predictive prognosticator of the immune response

SARPPIC: Exploiting COVID19 Contact Tracing Recommendation through Social Awareness Comput. Math. Method Med. (IF 1.77) Pub Date : 20201116
Nana Yaw Asabere; Amevi Acakpovi; Emmanuel Kwaku Ofori; Wisdom Torgby; Marcellinus Kuuboore; Gare Lawson; Edward AdjalokoGlobally, the current coronavirus disease 2019 (COVID19) pandemic is resulting in high fatality rates. Consequently, the prevention of further transmission is very vital. Until vaccines are widely available, the only available infection prevention methods include the following: contact tracing, case isolation and quarantine, social (physical) distancing, and hygiene measures (washing of hands with

Succinylation Site Prediction Based on Protein Sequences Using the IFSLightGBM (BO) Model Comput. Math. Method Med. (IF 1.77) Pub Date : 20201111
Lu Zhang; Min Liu; Xinyi Qin; Guangzhong LiuSuccinylation is an important posttranslational modification of proteins, which plays a key role in protein conformation regulation and cellular function control. Many studies have shown that succinylation modification on protein lysine residue is closely related to the occurrence of many diseases. To understand the mechanism of succinylation profoundly, it is necessary to identify succinylation sites

The Use of System Dynamics Methodology in Building a COVID19 Confirmed Case Model Comput. Math. Method Med. (IF 1.77) Pub Date : 20201110
Mohd Izhan Mohd YusoffResearchers used a hybrid model (a combination of health resource demand model and disease transmission model), Bayesian model, and susceptibleexposedinfectiousremoved (SEIR) model to predict health service utilization and deaths and mixedeffect nonlinear regression. Further, they used the mixture model to predict the number of confirmed cases and deaths or to predict when the curve would flatten

A Multifeature Extraction Method Using Deep Residual Network for MR Image Denoising Comput. Math. Method Med. (IF 1.77) Pub Date : 20201106
Li YaoIn order to improve the resolution of magnetic resonance (MR) image and reduce the interference of noise, a multifeature extraction denoising algorithm based on a deep residual network is proposed. First, the feature extraction layer is constructed by combining three different sizes of convolution kernels, which are used to obtain multiple shallow features for fusion and increase the network’s multiscale

miR1395p Inhibits Lung Adenocarcinoma Cell Proliferation, Migration, and Invasion by Targeting MAD2L1 Comput. Math. Method Med. (IF 1.77) Pub Date : 20201104
Jianfeng Li; Xi He; Xiaotang Wu; Xiaohui Liu; Yixiong Huang; Yuchen GongBackground. miR1395p is lowly expressed in various human cancers and exerts its antitumor effect through different molecular mechanisms, yet the molecular mechanism of miR1395p in lung adenocarcinoma (LUAD) remains to be further elucidated. The study is aimed at investigating the role and the regulatory mechanism of miR1395p in LUAD progression. Methods. Differential analysis was performed on

Segmentation of IntensityCorrupted Medical Images Using Adaptive WeightBased Hybrid Active Contours Comput. Math. Method Med. (IF 1.77) Pub Date : 20201104
Asif Aziz Memon; Shafiullah Soomro; Muhammad Tanseef Shahid; Asad Munir; Asim Niaz; Kwang Nam ChoiSegmentation accuracy is an important criterion for evaluating the performance of segmentation techniques used to extract objects of interest from images, such as the active contour model. However, segmentation accuracy can be affected by image artifacts such as intensity inhomogeneity, which makes it difficult to extract objects with inhomogeneous intensities. To address this issue, this paper proposes

An Integrating ImmuneRelated Signature to Improve Prognosis of Hepatocellular Carcinoma Comput. Math. Method Med. (IF 1.77) Pub Date : 20201103
Rui Zhu; Wenna Guo; XinJian Xu; Liucun ZhuGrowing evidence suggests that the superiority of long noncoding RNAs (lncRNAs) and messenger RNAs (mRNAs) could act as biomarkers for cancer prognosis. However, the prognostic marker for hepatocellular carcinoma with high accuracy and sensitivity is still lacking. In this research, a retrospective, cohortbased study of genomewide RNAseq data of patients with hepatocellular carcinoma was carried

DRGOriented Mathematical Calculation Model and Method of Integrated Medical Service Cost Comput. Math. Method Med. (IF 1.77) Pub Date : 20201102
Xiaowei Sun; Yi ZhuIn the context of the new round of medical and health reform, in order to alleviate the problem of “difficult to see a doctor and expensive to see a doctor,” the state focuses on reducing the cost of medical services, so it puts forward the calculation and method research of medical costs. The purpose of this study is to calculate and predict the cost of medical services in a DRGoriented integrated

Comprehensive Analysis of Differently Expressed and Methylated Genes in Preeclampsia Comput. Math. Method Med. (IF 1.77) Pub Date : 20201102
Wenyi Xu; Ping Ru; Zhuorong Gu; Ruoxi Zhang; Xixia Pang; Yi Huang; Zhou Liu; Ming LiuPreeclampsia (PE) is one of the mainly caused maternal and infant incidences and mortalities worldwide. However, the mechanisms underlying PE remained largely unclear. The present study identified 1716 high expressions of gene and 2705 low expressions of gene using GSE60438 database, and identified 7087 hypermethylated and 15120 hypomethylated genes in preeclampsia using GSE100197. Finally, 536 upregulated

Modelling the Potential Impact of Social Distancing on the COVID19 Epidemic in South Africa Comput. Math. Method Med. (IF 1.77) Pub Date : 20201030
F. Nyabadza; F. Chirove; C. W. Chukwu; M. V. VisayaThe novel coronavirus (COVID19) pandemic continues to be a global health problem whose impact has been significantly felt in South Africa. With the global spread increasing and infecting millions, containment efforts by countries have largely focused on lockdowns and social distancing to minimise contact between persons. Social distancing has been touted as the best form of response in managing a

Using Convolutional Neural Network with Cheat Sheet and Data Augmentation to Detect Breast Cancer in Mammograms Comput. Math. Method Med. (IF 1.77) Pub Date : 20201028
Saleem Z. RamadanThe American Cancer Society expected to diagnose 276,480 new cases of invasive breast cancer in the USA and 48,530 new cases of noninvasive breast cancer among women in 2020. Early detection of breast cancer, followed by appropriate treatment, can reduce the risk of death from this disease. DL through CNN can assist imaging specialists in classifying the mammograms accurately. Accurate classification

Gene Expression Profiling of Type 2 Diabetes Mellitus by Bioinformatics Analysis Comput. Math. Method Med. (IF 1.77) Pub Date : 20201023
Huijing Zhu; Xin Zhu; Yuhong Liu; Fusong Jiang; Miao Chen; Lin Cheng; Xingbo ChengObjective. The aim of this study was to identify the candidate genes in type 2 diabetes mellitus (T2DM) and explore their potential mechanisms. Methods. The gene expression profile GSE26168 was downloaded from the Gene Expression Omnibus (GEO) database. The online tool GEO2R was used to obtain differentially expressed genes (DEGs). Gene Ontology (GO) term enrichment analysis and Kyoto Encyclopedia

A Simple Framework of Smart Geriatric Nursing considering Health Big Data and User Profile Comput. Math. Method Med. (IF 1.77) Pub Date : 20201023
Shijie Li; Yongchuan TangThe National Bureau of Statistics of China shows that the population over 65 years old in China exceeds 166 million accounting for 11.93% of the total population by the end of 2018. The importance and severity of taking care of the elderly are becoming increasingly prominent. Highquality and meticulous care for the daily life of the elderly needs helpful and advanced sciences and technologies. Smart

Polygonally Meshed Dipole Model Simulation of the Electrical Field Produced by the Stomach and Intestines Comput. Math. Method Med. (IF 1.77) Pub Date : 20201021
Masaki Kawano; Takahiro EmotoCutaneous electrogastrography (EGG) is used in clinical and physiological fields to noninvasively measure the electrical activity of the stomach and intestines. Dipole models that mathematically express the electrical field characteristics generated by the stomach and intestines have been developed to investigate the relationship between the electrical control activity (ECA) (slow waves) shown in EGG

Evaluation of Multimodal Algorithms for the Segmentation of Multiparametric MRI Prostate Images Comput. Math. Method Med. (IF 1.77) Pub Date : 20201021
YingHwey Nai; Bernice W. Teo; Nadya L. Tan; Koby Yi Wei Chua; Chun Kit Wong; Sophie O’Doherty; Mary C. Stephenson; Josh Schaefferkoetter; Yee Liang Thian; Edmund Chiong; Anthonin ReilhacProstate segmentation in multiparametric magnetic resonance imaging (mpMRI) can help to support prostate cancer diagnosis and therapy treatment. However, manual segmentation of the prostate is subjective and timeconsuming. Many deep learning monomodal networks have been developed for automatic whole prostate segmentation from T2weighted MR images. We aimed to investigate the added value of multimodal

circFAT1(e2) Promotes Papillary Thyroid Cancer Proliferation, Migration, and Invasion via the miRNA873/ZEB1 Axis Comput. Math. Method Med. (IF 1.77) Pub Date : 20201020
Jiazhe Liu; Hongchang Li; Chuanchao Wei; Junbin Ding; Jingfeng Lu; Gaofeng Pan; Anwei MaoCircular RNAs (circRNAs) play an extremely important regulatory role in the occurrence and development of various malignant tumors including papillary thyroid cancer (PTC). circFAT1(e2) is a new type of circRNA derived from exon 2 of the FAT1 gene, which is distributed in the cytoplasm and nucleus of PTC cells. However, so far, the role of circFAT1(e2) in PTC is still unclear. In this study, circFAT1(e2)

Phenomenological Modelling of COVID19 Epidemics in Sri Lanka, Italy, the United States, and Hebei Province of China Comput. Math. Method Med. (IF 1.77) Pub Date : 20201019
A. M. C. H. Attanayake; S. S. N. Perera; S. JayasingheThe COVID19 pandemic has resulted in increasing number of infections and deaths every day. Lack of specialized treatments for the disease demands preventive measures based on statistical/mathematical models. The analysis of epidemiological curve fitting, on number of daily infections across affected countries, provides useful insights on the characteristics of the epidemic. A variety of phenomenological

COVID19 Epidemic in Sri Lanka: A Mathematical and Computational Modelling Approach to Control Comput. Math. Method Med. (IF 1.77) Pub Date : 20201019
W. P. T. M. Wickramaarachchi; S. S. N. Perera; S. JayasingheThe ongoing COVID19 outbreak that originated in the city of Wuhan, China, has caused a significant damage to the world population and the global economy. It has claimed more than 0.8 million lives worldwide, and more than 27 million people have been infected as of 07th September 2020. In Sri Lanka, the first case of COVID19 was reported late January 2020 which was a Chinese national and the first

Identification and Classification of Enhancers Using Dimension Reduction Technique and Recurrent Neural Network Comput. Math. Method Med. (IF 1.77) Pub Date : 20201019
Qingwen Li; Lei Xu; Qingyuan Li; Lichao ZhangEnhancers are noncoding fragments in DNA sequences, which play an important role in gene transcription and translation. However, due to their high free scattering and positional variability, the identification and classification of enhancers have a higher level of complexity than those of coding genes. In order to solve this problem, many computer studies have been carried out in this field, but there

A Method for Identifying Vesicle Transport Proteins Based on LibSVM and MRMD Comput. Math. Method Med. (IF 1.77) Pub Date : 20201019
Zhiyu Tao; Yanjuan Li; Zhixia Teng; Yuming ZhaoWith the development of computer technology, many machine learning algorithms have been applied to the field of biology, forming the discipline of bioinformatics. Protein function prediction is a classic research topic in this subject area. Though many scholars have made achievements in identifying protein by different algorithms, they often extract a large number of feature types and use very complex

Modeling the Impact of Seasonal Weather Variations on the Infectiology of Brucellosis Comput. Math. Method Med. (IF 1.77) Pub Date : 20201017
Nkuba Nyerere; Livingstone S. Luboobi; Saul C. Mpeshe; Gabriel M. ShirimaA deterministic mathematical model for brucellosis that incorporates seasonality on direct and indirect transmission parameters for domestic ruminants, wild animals, humans, and the environment was formulated and analyzed in this paper. Both analytical and numerical simulations are presented. From this study, the findings show that variations in seasonal weather have the great impact on the transmission

Identification of an Epidemiological Model to Simulate the COVID19 Epidemic Using Robust Multiobjective Optimization and Stochastic Fractal Search Comput. Math. Method Med. (IF 1.77) Pub Date : 20201015
Fran Sérgio Lobato; Gustavo Barbosa Libotte; Gustavo Mendes PlattTraditionally, the identification of parameters in the formulation and solution of inverse problems considers that models, variables, and mathematical parameters are free of uncertainties. This aspect simplifies the estimation process, but does not consider the influence of relatively small changes in the design variables in terms of the objective function. In this work, the SIDR (Susceptible, Infected

Imrecoxib Inhibits ParaquatInduced Pulmonary Fibrosis through the NFκB/Snail Signaling Pathway Comput. Math. Method Med. (IF 1.77) Pub Date : 20201014
Haihao JinObjective. In recent years, pulmonary fibrosis caused by paraquat poisoning is still concerned. However, no effective drugs have been developed yet to treat paraquatinduced pulmonary fibrosis. The aim of our research is to investigate whether imrecoxib can inhibit paraquatinduced pulmonary fibrosis and its possible mechanism. Methods. Extraction of primary pulmonary fibrosis cells (PPF cells) in

A Mathematical Model to Study the Effectiveness of Some of the Strategies Adopted in Curtailing the Spread of COVID19 Comput. Math. Method Med. (IF 1.77) Pub Date : 20201013
Isa Abdullahi Baba; Bashir Abdullahi Baba; Parvaneh EsmailiIn this paper, we developed a model that suggests the use of robots in identifying COVID19positive patients and which studied the effectiveness of the government policy of prohibiting migration of individuals into their countries especially from those countries that were known to have COVID19 epidemic. Two compartmental models consisting of two equations each were constructed. The models studied

A Mathematical Model to Investigate the Transmission of COVID19 in the Kingdom of Saudi Arabia Comput. Math. Method Med. (IF 1.77) Pub Date : 20201012
Fehaid Salem AlshammariSince the first confirmed case of SARSCoV2 coronavirus (COVID19) on March 02, 2020, Saudi Arabia has not reported quite a rapid COVD19 spread as seen in America and many European countries. Possible causes include the spread of asymptomatic COVID19 cases. To characterize the transmission of COVID19 in Saudi Arabia, a susceptible, exposed, symptomatic, asymptomatic, hospitalized, and recovered

Effects of Bronchoalveolar Lavage with Ambroxol Hydrochloride on Treating Pulmonary Infection in Patients with Cerebral Infarction and on Serum Proinflammatory Cytokines, MDA and SOD Comput. Math. Method Med. (IF 1.77) Pub Date : 20201009
Fanhua Meng; Jing Cheng; Peng Sang; Jianhui WangObjective. This paper was aimed at investigating the effects of bronchoalveolar lavage (BAL) with ambroxol hydrochloride (AH) on treating pulmonary infection and on serum proinflammatory cytokines and oxidative stress responses in patients with cerebral infarction (CI). Methods. One hundred and two patients with cerebral infarction complicated with pulmonary infection (CIPI) who were treated in our

Wavelet Scattering Transform for ECG Beat Classification Comput. Math. Method Med. (IF 1.77) Pub Date : 20201009
Zhishuai Liu; Guihua Yao; Qing Zhang; Junpu Zhang; Xueying ZengAn electrocardiogram (ECG) records the electrical activity of the heart; it contains rich pathological information on cardiovascular diseases, such as arrhythmia. However, it is difficult to visually analyze ECG signals due to their complexity and nonlinearity. The wavelet scattering transform can generate translationinvariant and deformationstable representations of ECG signals through cascades

Texture FeatureBased Classification on Transrectal Ultrasound Image for Prostatic Cancer Detection Comput. Math. Method Med. (IF 1.77) Pub Date : 20201006
Xiaofu Huang; Ming Chen; Peizhong Liu; Yongzhao DuProstate cancer is one of the most common cancers in men. Early detection of prostate cancer is the key to successful treatment. Ultrasound imaging is one of the most suitable methods for the early detection of prostate cancer. Although ultrasound images can show cancer lesions, subjective interpretation is not accurate. Therefore, this paper proposes a transrectal ultrasound image analysis method

Mathematical Modelling of HIVHCV Coinfection Dynamics in Absence of Therapy Comput. Math. Method Med. (IF 1.77) Pub Date : 20201006
Edison Mayanja; Livingstone S. Luboobi; Juma Kasozi; Rebecca N. NsubugaGlobally, it is estimated that of the 36.7 million people infected with human immunodeficiency virus (HIV), 6.3% are coinfected with hepatitis C virus (HCV). Coinfection with HIV reduces the chance of HCV spontaneous clearance. In this work, we formulated and analysed a deterministic model to study the HIV and HCV coinfection dynamics in absence of therapy. Due to chronic stage of HCV infection being

Effects of SingleNucleotide Polymorphisms in CalmodulinDependent Protein Kinase Kinase 2 (CAMKK2): A Comprehensive Study Comput. Math. Method Med. (IF 1.77) Pub Date : 20201006
Zoya Khalid; Omar AlmaghrabiCalmodulindependent protein kinase kinase 2 (CAMKK2) is a protein kinase that belongs to the serine/threonine kinase family. It phosphorylates kinases like CAMK1, CAMK2, and AMP, and this signaling cascade is involved in various biological processes including cell proliferation, apoptosis, and proliferation. Also, the CAMKK2 signaling activity is required for the healthy activity of the brain which

Transcriptome Analysis Identifies Novel Prognostic Genes in Osteosarcoma Comput. Math. Method Med. (IF 1.77) Pub Date : 20201006
Junfeng Chen; Xiaojun Guo; Guangjun Zeng; Jianhua Liu; Bin ZhaoOsteosarcoma (OS), a malignant primary bone tumor often seen in young adults, is highly aggressive. The improvements in highthroughput technologies have accelerated the identification of various prognostic biomarkers for cancer survival prediction. However, only few studies focus on the prediction of prognosis in OS patients using gene expression data due to small sample size and the lack of public

A Medical Decision Support System to Assess Risk Factors for Gastric Cancer Based on Fuzzy Cognitive Map Comput. Math. Method Med. (IF 1.77) Pub Date : 20201005
Seyed Abbas Mahmoodi; Kamal Mirzaie; Maryam Sadat Mahmoodi; Seyed Mostafa MahmoudiGastric cancer (GC), one of the most common cancers around the world, is a multifactorial disease and there are many risk factors for this disease. Assessing the risk of GC is essential for choosing an appropriate healthcare strategy. There have been very few studies conducted on the development of risk assessment systems for GC. This study is aimed at providing a medical decision support system based

Penalized Quadratic Inference FunctionBased Variable Selection for Generalized Partially Linear Varying Coefficient Models with Longitudinal Data Comput. Math. Method Med. (IF 1.77) Pub Date : 20201005
Jinghua Zhang; Liugen XueSemiparametric generalized varying coefficient partially linear models with longitudinal data arise in contemporary biology, medicine, and life science. In this paper, we consider a variable selection procedure based on the combination of the basis function approximations and quadratic inference functions with SCAD penalty. The proposed procedure simultaneously selects significant variables in the