The EEG-Based Attention Analysis in Multimedia m-Learning.
In this study, EEG experiment of a group of iPad-based 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 in learners' attention. The study found no significant difference in attention in different media, but learners using text media had the highest attention value. Later, the researchers studied the attention of learners with different learning styles and found that active and reflective learners' attention exhibited significant differences when using video media to learn. PMID: 325876...
Source: Computational and Mathematical Methods in Medicine - June 27, 2020 Category: Statistics Tags: Comput Math Methods Med Source Type: research

Improved Kaplan-Meier Estimator in Survival Analysis Based on Partially Rank-Ordered Set Samples.
This 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 Rank-Ordered 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 sampling units is costly; however, sampling units can be ordered by using judgment ranking or available concomitant information. The general estimation methods are not directly applicable to the case where samples are from rank-...
Source: Computational and Mathematical Methods in Medicine - June 27, 2020 Category: Statistics Tags: Comput Math Methods Med Source Type: research

Electrical Impedance Tomography-Based Abdominal Subcutaneous Fat Estimation Method Using Deep Learning.
Authors: Lee K, Yoo M, Jargal A, Kwon H Abstract This 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 current-to-voltage data. Existing reconstruction methods based on EIT have difficulty handling the inherent drawbacks of strong nonlinearity and severe ill-posedness of EIT; hence, absolute imaging may not be possible using linearized methods. To handle nonlinearity and i...
Source: Computational and Mathematical Methods in Medicine - June 27, 2020 Category: Statistics Tags: Comput Math Methods Med Source Type: research

Influences of Daily Life Habits on Risk Factors of Stroke Based on Decision Tree and Correlation Matrix.
Conclusions: Establishment of a model for stroke risk assessment, analysis of factors influencing risk factors of stroke, analysis of relationships among those factors, and derivation of knowledge-based rules are helpful for prevention and treatment of stroke. PMID: 32565878 [PubMed - in process] (Source: Computational and Mathematical Methods in Medicine)
Source: Computational and Mathematical Methods in Medicine - June 24, 2020 Category: Statistics Tags: Comput Math Methods Med Source Type: research

A Game Theory-Based Model for Predicting Depression due to Frustration in Competitive Environments.
Authors: Loula R, Monteiro LHA Abstract A 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 well-known prisoner's dilemma, represents the payoffs that can be received by the individuals in the labor market. These individuals may or may not have invested in a formal academic education. It is assumed that an individual becomes depressed when the difference between the average payoff ...
Source: Computational and Mathematical Methods in Medicine - June 24, 2020 Category: Statistics Tags: Comput Math Methods Med Source Type: research

CUL1-Mediated Organelle Fission Pathway Inhibits the Development of Chronic Obstructive Pulmonary Disease.
Authors: Li R, Xu F, Wu X, Ji S, Xia R Abstract Chronic obstructive pulmonary disease (COPD) is a global high-incidence 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 in-depth analysis of transcription factors and ncRNA-driven pathogenic modules of COPD. We obtained the expression profile of COPD-related microRNAs from the NCBI-GEO database and analy...
Source: Computational and Mathematical Methods in Medicine - June 24, 2020 Category: Statistics Tags: Comput Math Methods Med Source Type: research

A Lead Field Two-Domain Model for Longitudinal Neural Tracts-Analytical Framework and Implications for Signal Bandwidth.
We present a theoretical framework which allows computing the electric potential generated by a single axon in a body surface lead by the convolution of the neural lead field function with a propagating action potential term. The signal generated by a large cohort of axons was obtained by convoluting a single axonal signal with the statistical distribution of temporal dispersion of individual axonal signals. For establishing the framework, analysis was based on an analytical model. Our approach was further adopted for a numerical computation of body surface neuropotentials employing the lead field theory. Double convolutio...
Source: Computational and Mathematical Methods in Medicine - June 24, 2020 Category: Statistics Tags: Comput Math Methods Med Source Type: research

Modeling the Spread of COVID-19 Infection Using a Multilayer Perceptron.
Authors: Car Z, Baressi Šegota S, Anđelić N, Lorencin I, Mrzljak V Abstract Coronavirus (COVID-19) 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 information on infected, recovered, and deceased patients in 406 locations over 51 days (22nd January 2020 to 12th March 2020)...
Source: Computational and Mathematical Methods in Medicine - June 24, 2020 Category: Statistics Tags: Comput Math Methods Med Source Type: research

A Global Inhomogeneous Intensity Clustering- (GINC-) Based Active Contour Model for Image Segmentation and Bias Correction.
Authors: Feng C, Yang J, Lou C, Li W, Yu K, Zhao D Abstract Image 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 of the image intensities, and membership functions of the clusters described by the level set function are then introduced to define the data term energ...
Source: Computational and Mathematical Methods in Medicine - June 24, 2020 Category: Statistics Tags: Comput Math Methods Med Source Type: research

Modeling the Influence of Nonclinic Visits on the Transmission of Respiratory Diseases.
Authors: Bao Y, Xu Y, Qi L, Zhai S Abstract According 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 qualitative theory of the model was analyzed to obtain the basic reproduction number R 0, disease-free equilibrium, endemic equilibrium, and stability of two equilibriums. ...
Source: Computational and Mathematical Methods in Medicine - June 24, 2020 Category: Statistics Tags: Comput Math Methods Med Source Type: research

A Novel 3D Reconstruction Algorithm of Motion-Blurred CT Image.
Authors: Jing Z, Qiang G, Fang H, Zhan-Li L, Hong-An L, Yu S Abstract The majority of medical workers are eager to obtain realistic and real-time CT 3D reconstruction results. However, autonomous or involuntary motion of patients can cause blurring of CT images. For the 3D reconstruction scene of motion-blurred CT image, this paper consists of two parts: firstly, a GAN image translation network deblurring algorithm is proposed to remove blurred results. This algorithm adopts the clear image to supervise the training process of the blurred image, which creates solutions that are close to the clear image. Secondly, t...
Source: Computational and Mathematical Methods in Medicine - June 24, 2020 Category: Statistics Tags: Comput Math Methods Med Source Type: research

High-Throughput Docking and Molecular Dynamics Simulations towards the Identification of Potential Inhibitors against Human Coagulation Factor XIIa.
Authors: Xu D, Xue G, Peng B, Feng Z, Lu H, Gong L Abstract Human coagulation factor XIIa (FXIIa) is a trypsin-like 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 high-throughput screening of 500,064 compounds within Enamine database to acquire the most potential inhibitors of FXIIa. Subsequently, 18 compounds with significant binding energy (from -65.195 to -15.726 kcal/mol) were selected, and their ADMET properties were predicted to sele...
Source: Computational and Mathematical Methods in Medicine - June 20, 2020 Category: Statistics Tags: Comput Math Methods Med Source Type: research

A New Extended-X Family of Distributions: Properties and Applications.
Authors: Zichuan M, Hussain S, Iftikhar A, Ilyas M, Ahmad Z, Khan DM, Manzoor S Abstract During 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. Well-known distributions are log-normal, log-t, various versions of Pareto, log-logistic, Weibull, gamma, exponential, Rayleigh and its variants, and generalized beta of the second kind distributions, among others. In this paper, we try to supplement the ...
Source: Computational and Mathematical Methods in Medicine - June 20, 2020 Category: Statistics Tags: Comput Math Methods Med Source Type: research

Construction and Analysis of Double Helix for Triangular Bipyramid and Pentangular Bipyramid.
This study may obtain some new insights into the DNA assembly from the viewpoint of mathematics, promoting the comprehending and design efficiency of DNA polyhedra with required topological structures. PMID: 32549907 [PubMed - in process] (Source: Computational and Mathematical Methods in Medicine)
Source: Computational and Mathematical Methods in Medicine - June 20, 2020 Category: Statistics Tags: Comput Math Methods Med Source Type: research

Association between Timing of Surgical Intervention and Mortality in 15,813 Acute Pancreatitis.
Conclusion: There is an L-shaped relationship between timing of surgical intervention and risk of death in necrotizing pancreatitis. PMID: 32508973 [PubMed - in process] (Source: Computational and Mathematical Methods in Medicine)
Source: Computational and Mathematical Methods in Medicine - June 10, 2020 Category: Statistics Tags: Comput Math Methods Med Source Type: research

Interpretable Learning Approaches in Resting-State Functional Connectivity Analysis: The Case of Autism Spectrum Disorder.
Authors: Hu J, Cao L, Li T, Liao B, Dong S, Li P Abstract Deep 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 functional magnetic resonance imaging (fMRI) data and interpret results of the model in a precise and consistent manner. First, we propose an interpretable fully ...
Source: Computational and Mathematical Methods in Medicine - June 10, 2020 Category: Statistics Tags: Comput Math Methods Med Source Type: research

EEG Signal and Feature Interaction Modeling-Based Eye Behavior Prediction Research.
Authors: Ma P, Gao Q Abstract In 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 of analyzing the characteristics of user interaction, we can use EEG data to predict the binomial state of eyes (open eyes and closed eyes). The significance of the research is that we can d...
Source: Computational and Mathematical Methods in Medicine - June 10, 2020 Category: Statistics Tags: Comput Math Methods Med Source Type: research

Auxiliary Medical Decision System for Prostate Cancer Based on Ensemble Method.
Authors: Wu J, Zhuang Q, Tan Y Abstract Prostate 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 employed classical machine learning models (support vector machine and artificial neural network). Stacking method aimed at different ensemble models together was used for the re...
Source: Computational and Mathematical Methods in Medicine - June 10, 2020 Category: Statistics Tags: Comput Math Methods Med Source Type: research

Development and Application of One Separation-Free Safety Tube on the Disposable Infusion Needle.
Authors: Lu W, Pan Q, Zhou Y, Chen W, Zhang H, Qi W Abstract Objective: 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 separation-free safety tube were used in the intervention group, whereas conventional ones were used in the control group. Then, effects of the two types of infusion...
Source: Computational and Mathematical Methods in Medicine - June 10, 2020 Category: Statistics Tags: Comput Math Methods Med Source Type: research

Multichart Schemes for Detecting Changes in Disease Incidence.
Authors: Engmann GM, Han D Abstract Several methods have been proposed in open literatures for detecting changes in disease outbreak or incidence. Most of these methods are likelihood-based as well as the direct application of Shewhart, CUSUM and EWMA schemes. We use CUSUM, EWMA and EWMA-CUSUM multi-chart schemes to detect changes in disease incidence. Multi-chart is a combination of several single charts that detects changes in a process and have been shown to have elegant properties in the sense that they are fast in detecting changes in a process as well as being computationally less expensive. Simulation result...
Source: Computational and Mathematical Methods in Medicine - June 10, 2020 Category: Statistics Tags: Comput Math Methods Med Source Type: research

Prediction of Drug Side Effects with a Refined Negative Sample Selection Strategy.
In this study, a novel negative sample selection strategy was designed for accessing high-quality negative samples. Such strategy applied the random walk with restart (RWR) algorithm on a chemical-chemical interaction network to select pairs of drugs and side effects, such that drugs were less likely to have corresponding side effects, as negative samples. Through several tests with a fixed feature extraction scheme and different machine-learning algorithms, models with selected negative samples produced high performance. The best model even yielded nearly perfect performance. These models had much higher performance than ...
Source: Computational and Mathematical Methods in Medicine - May 28, 2020 Category: Statistics Tags: Comput Math Methods Med Source Type: research

Automatic Segmentation and Measurement on Knee Computerized Tomography Images for Patellar Dislocation Diagnosis.
Authors: Sun L, Kong Q, Huang Y, Yang J, Wang S, Zou R, Yin Y, Peng J Abstract Traditionally, for diagnosing patellar dislocation, clinicians make manual geometric measurements on computerized tomography (CT) images taken in the knee area, which is often complex and error-prone. Therefore, we develop a prototype CAD system for automatic measurement and diagnosis. We firstly segment the patella and the femur regions on the CT images and then measure two geometric quantities, patellar tilt angle (PTA), and patellar lateral shift (PLS) automatically on the segmentation results, which are finally used to assist in diag...
Source: Computational and Mathematical Methods in Medicine - May 28, 2020 Category: Statistics Tags: Comput Math Methods Med Source Type: research

Deep Convolutional Neural Networks-Based Automatic Breast Segmentation and Mass Detection in DCE-MRI.
Authors: Jiao H, Jiang X, Pang Z, Lin X, Huang Y, Li L Abstract Breast segmentation and mass detection in medical images are important for diagnosis and treatment follow-up. Automation of these challenging tasks can assist radiologists by reducing the high manual workload of breast cancer analysis. In this paper, deep convolutional neural networks (DCNN) were employed for breast segmentation and mass detection in dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). First, the region of the breasts was segmented from the remaining body parts by building a fully convolutional neural network based on U-Net+...
Source: Computational and Mathematical Methods in Medicine - May 28, 2020 Category: Statistics Tags: Comput Math Methods Med Source Type: research

Multicenter Computer-Aided Diagnosis for Lymph Nodes Using Unsupervised Domain-Adaptation Networks Based on Cross-Domain Confounding Representations.
Authors: Qin R, Zhang H, Jiang L, Qiao K, Hai J, Chen J, Xu J, Shi D, Yan B Abstract To achieve the robust high-performance computer-aided diagnosis systems for lymph nodes, CT images may be typically collected from multicenter data, which cause the isolated performance of the model based on different data source centers. The variability adaptation problem of lymph node data which is related to the problem of domain adaptation in deep learning differs from the general domain adaptation problem because of the typically larger CT image size and more complex data distributions. Therefore, domain adaptation for this pr...
Source: Computational and Mathematical Methods in Medicine - May 28, 2020 Category: Statistics Tags: Comput Math Methods Med Source Type: research

Fast Enhanced Exemplar-Based Clustering for Incomplete EEG Signals.
Authors: Bi A, Ying W, Zhao L Abstract The diagnosis and treatment of epilepsy is a significant direction for both machine learning and brain science. This paper newly proposes a fast enhanced exemplar-based clustering (FEEC) method for incomplete EEG signal. The algorithm first compresses the potential exemplar list and reduces the pairwise similarity matrix. By processing the most complete data in the first stage, FEEC then extends the few incomplete data into the exemplar list. A new compressed similarity matrix will be constructed and the scale of this matrix is greatly reduced. Finally, FEEC optimizes the new ...
Source: Computational and Mathematical Methods in Medicine - May 28, 2020 Category: Statistics Tags: Comput Math Methods Med Source Type: research

High-Biofidelity Biomodel Generated from Three-Dimensional Imaging (Cone-Beam Computed Tomography): A Methodological Proposal.
Authors: Hernández-Vázquez RA, Urriolagoitia-Sosa G, Marquet-Rivera RA, Romero-Ángeles B, Mastache-Miranda OA, Vázquez-Feijoo JA, Urriolagoitia-Calderón G Abstract Experimental research on living beings faces several obstacles, which are more than ethical and moral issues. One of the proposed solutions to these situations is the computational modelling of anatomical structures. The present study shows a methodology for obtaining high-biofidelity biomodels, where a novel imagenological technique is used, which applies several CAM/CAD computer programs that allow a better precision ...
Source: Computational and Mathematical Methods in Medicine - May 28, 2020 Category: Statistics Tags: Comput Math Methods Med Source Type: research

A Novel Radial Basis Neural Network-Leveraged Fast Training Method for Identifying Organs in MR Images.
Authors: Xu M, Qian P, Zheng J, Ge H, Muzic RF Abstract We propose a new method for fast organ classification and segmentation of abdominal magnetic resonance (MR) images. Magnetic resonance imaging (MRI) is a new type of high-tech imaging examination fashion in recent years. Recognition of specific target areas (organs) based on MR images is one of the key issues in computer-aided diagnosis of medical images. Artificial neural network technology has made significant progress in image processing based on the multimodal MR attributes of each pixel in MR images. However, with the generation of large-scale data, there...
Source: Computational and Mathematical Methods in Medicine - May 28, 2020 Category: Statistics Tags: Comput Math Methods Med Source Type: research

Cross-Subject Seizure Detection in EEGs Using Deep Transfer Learning.
Authors: Zhang B, Wang W, Xiao Y, Xiao S, Chen S, Chen S, Xu G, Che W Abstract Electroencephalography (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 task of seizure detection much challenging, for both human experts and automation methods. We propose three deep transfer convolutional neural...
Source: Computational and Mathematical Methods in Medicine - May 28, 2020 Category: Statistics Tags: Comput Math Methods Med Source Type: research

Fusion of FDG-PET Image and Clinical Features for Prediction of Lung Metastasis in Soft Tissue Sarcomas.
Authors: Deng J, Zeng W, Shi Y, Kong W, Guo S Abstract Extracting massive features from images to quantify tumors provides a new insight to solve the problem that tumor heterogeneity is difficult to assess quantitatively. However, quantification of tumors by single-mode methods often has defects such as difficulty in features extraction and high computational complexity. The multimodal approach has shown effective application prospects in solving these problems. In this paper, we propose a feature fusion method based on positron emission tomography (PET) images and clinical information, which is used to obtain feat...
Source: Computational and Mathematical Methods in Medicine - May 28, 2020 Category: Statistics Tags: Comput Math Methods Med Source Type: research

Fluid Structure Interaction on Paravalvular Leakage of Transcatheter Aortic Valve Implantation Related to Aortic Stenosis: A Patient-Specific Case.
This study investigated the impact of paravalvular leakage (PVL) in relation to the different valve openings of the transcatheter aortic valve implantation (TAVI) valve using the fluid structure interaction (FSI) approach. Limited studies were found on the subject of FSI with regards to TAVI-PVL condition, which involves both fluid and structural responses in coupling interaction. Hence, further FSI simulation with the two-way coupling method is implemented to investigate the effects of hemodynamics blood flow along the patient-specific aorta model subjected to the interrelationship between PVL and the different valve open...
Source: Computational and Mathematical Methods in Medicine - May 28, 2020 Category: Statistics Tags: Comput Math Methods Med Source Type: research

A Fast Subpixel Registration Algorithm Based on Single-Step DFT Combined with Phase Correlation Constraint in Multimodality Brain Image.
Authors: Li J, Ma Q Abstract Multimodality brain image registration technology is the key technology to determine the accuracy and speed of brain diagnosis and treatment. In order to achieve high-precision image registration, a fast subpixel registration algorithm based on single-step DFT combined with phase correlation constraint in multimodality brain image was proposed in this paper. Firstly, the coarse positioning at the pixel level was achieved by using the downsampling cross-correlation model, which reduced the Fourier transform dimension of the cross-correlation matrix and the multiplication of the discrete ...
Source: Computational and Mathematical Methods in Medicine - May 28, 2020 Category: Statistics Tags: Comput Math Methods Med Source Type: research

Using Eye Aspect Ratio to Enhance Fast and Objective Assessment of Facial Paralysis.
In this study, patients with facial paralysis were enrolled as study objects, and the eye aspect ratio (EAR) index was proposed for the eye region. The correlation between EAR and the facial nerve grading system 2.0 (FNGS 2.0) score was analyzed to verify the ability of EAR to enhance FNGS 2.0 for the rapid and objective assessment of the severity of the facial paralysis. Firstly, in order to accurately calculate the EAR, we constructed a landmark detection model based on the face images of facial paralysis patients (FP-FLDM). Evaluation results showed that the error rate of facial feature point detection in patients with ...
Source: Computational and Mathematical Methods in Medicine - May 17, 2020 Category: Statistics Tags: Comput Math Methods Med Source Type: research

Magnetic Resonance Image Denoising Algorithm Based on Cartoon, Texture, and Residual Parts.
Authors: Zeng Y, Zhang B, Zhao W, Xiao S, Zhang G, Ren H, Zhao W, Peng Y, Xiao Y, Lu Y, Zong Y, Ding Y Abstract Magnetic resonance (MR) images are often contaminated by Gaussian noise, an electronic noise caused by the random thermal motion of electronic components, which reduces the quality and reliability of the images. This paper puts forward a hybrid denoising algorithm for MR images based on two sparsely represented morphological components and one residual part. To begin with, decompose a noisy MR image into the cartoon, texture, and residual parts by MCA, and then each part is denoised by using Wiener filter...
Source: Computational and Mathematical Methods in Medicine - May 17, 2020 Category: Statistics Tags: Comput Math Methods Med Source Type: research

Differential Diagnostic Reasoning Method for Benign Paroxysmal Positional Vertigo Based on Dynamic Uncertain Causality Graph.
This study further uses vertigo cases to test the performance of the proposed method in clinical practice. The results point to high accuracy, a satisfactory discriminatory ability for BPPV, and favorable robustness regarding incomplete medical information. The underlying pathological mechanisms and causality semantics are verified using compact graphical representation and reasoning process, which enhance the interpretability of the diagnosis conclusions. PMID: 32411277 [PubMed - in process] (Source: Computational and Mathematical Methods in Medicine)
Source: Computational and Mathematical Methods in Medicine - May 17, 2020 Category: Statistics Tags: Comput Math Methods Med Source Type: research

Epilepsy Detection in EEG Using Grassmann Discriminant Analysis Method.
Authors: Yu H, Fan C, Zhang Y Abstract Epilepsy is marked by seizures stemming from abnormal electrical activity in the brain, causing involuntary movement or behavior. Many scientists have been working hard to explore the cause of epilepsy and seek the prevention and treatment. In the field of machine learning, epileptic diagnosis based on EEG signal has been a very hot research topic; many methods have been proposed, and considerable progress has been achieved. However, resorting the epileptic diagnosis techniques based on EEG to the reality applications still faces many challenges. Low signal-to-noise ratio (SNR...
Source: Computational and Mathematical Methods in Medicine - May 17, 2020 Category: Statistics Tags: Comput Math Methods Med Source Type: research

A Combined Ultrasonic Backscatter Parameter for Bone Status Evaluation in Neonates.
This study firstly applied CAS to neonates, which was defined as a linear combination of the apparent integrated backscatter coefficient (AIB) and spectral centroid shift (SCS). The objective was to evaluate the feasibility of ultrasonic backscatter technique for assessing neonatal bone health using AIB, SCS, and CAS. Ultrasonic backscatter measurements at 3.5 MHz, 5.0 MHz, and 7.5 MHz were performed on a total of 505 newborns within 48 hours after birth. The values of backscatter parameters were calculated and compared among gestational age groups. Correlations between backscatter parameters, gestatio...
Source: Computational and Mathematical Methods in Medicine - May 17, 2020 Category: Statistics Tags: Comput Math Methods Med Source Type: research

Research of Multimodal Medical Image Fusion Based on Parameter-Adaptive Pulse-Coupled Neural Network and Convolutional Sparse Representation.
Authors: Xia J, Lu Y, Tan L Abstract Visual effects of medical image have a great impact on clinical assistant diagnosis. At present, medical image fusion has become a powerful means of clinical application. The traditional medical image fusion methods have the problem of poor fusion results due to the loss of detailed feature information during fusion. To deal with it, this paper proposes a new multimodal medical image fusion method based on the imaging characteristics of medical images. In the proposed method, the non-subsampled shearlet transform (NSST) decomposition is first performed on the source images to ob...
Source: Computational and Mathematical Methods in Medicine - May 17, 2020 Category: Statistics Tags: Comput Math Methods Med Source Type: research

Modeling the Spatiotemporal Dynamics of Oncolytic Viruses and Radiotherapy as a Treatment for Cancer.
Authors: Simbawa E, Al-Johani N, Al-Tuwairqi S Abstract Virotherapy is a novel treatment for cancer, which may be delivered as a single agent or in combination with other therapies. Research studies indicated that the combination of viral therapy and radiation therapy has synergistic antitumor effects in in vitro and in vivo. In this paper, we proposed two models in the form of partial differential equations to investigate the spatiotemporal dynamics of tumor cells under virotherapy and radiovirotherapy. We first presented a virotherapy model and solved it numerically for different values of the parameters related ...
Source: Computational and Mathematical Methods in Medicine - May 17, 2020 Category: Statistics Tags: Comput Math Methods Med Source Type: research

Robust Method for Semantic Segmentation of Whole-Slide Blood Cell Microscopic Images.
Authors: Shahzad M, Umar AI, Khan MA, Shirazi SH, Khan Z, Yousaf W Abstract Previous works on segmentation of SEM (scanning electron microscope) blood cell image ignore the semantic segmentation approach of whole-slide blood cell segmentation. In the proposed work, we address the problem of whole-slide blood cell segmentation using the semantic segmentation approach. We design a novel convolutional encoder-decoder framework along with VGG-16 as the pixel-level feature extraction model. The proposed framework comprises 3 main steps: First, all the original images along with manually generated ground truth masks of e...
Source: Computational and Mathematical Methods in Medicine - May 17, 2020 Category: Statistics Tags: Comput Math Methods Med Source Type: research

An Assessment of the Relationship between Structural and Functional Imaging of Cerebrovascular Disease and Cognition-Related Fibers.
Authors: Tang X, Xiao X, Yin J, Yang T, Zeng B Abstract In order to assess the relationship between structural and functional imaging of cerebrovascular disease and cognition-related fibers, this paper chooses a total of 120 patients who underwent cerebral small vessel disease (CSVD) treatment at a designated hospital by this study from June 2013 to June 2018 and divides them into 3 groups according to the random number table method: vascular dementia (VaD) group, vascular cognitive impairment no dementia (VCIND) group, and noncognition impairment (NCI) group with 40 cases of patients in each group. Cognitive funct...
Source: Computational and Mathematical Methods in Medicine - May 17, 2020 Category: Statistics Tags: Comput Math Methods Med Source Type: research

On the Chameleonic Behaviour of Cholesterol through a Fractal/Multifractal Model.
Authors: Tesloianu ND, Ghizdovat V, Agop M, Rusu C, Cardoneanu A Abstract An increasing number of studies are beginning to show that both low-density lipoprotein and high-density lipoprotein cholesterol can constitute risk factors for myocardial infarction. Such a behaviour has been called by experts in the field the "chameleonic effect" of cholesterol. In the present paper, a fractal/multifractal model for low-density lipoprotein and high-density lipoprotein cholesterol dynamics is proposed. In such a context, a fractal/multifractal tunneling effect for systems with spontaneous symmetry breaking is analy...
Source: Computational and Mathematical Methods in Medicine - May 17, 2020 Category: Statistics Tags: Comput Math Methods Med Source Type: research

DBT Masses Automatic Segmentation Using U-Net Neural Networks.
Authors: Lai X, Yang W, Li R Abstract To improve the automatic segmentation accuracy of breast masses in digital breast tomosynthesis (DBT) images, we propose a DBT mass automatic segmentation algorithm by using a U-Net architecture. Firstly, to suppress the background tissue noise and enhance the contrast of the mass candidate regions, after the top-hat transform of DBT images, a constraint matrix is constructed and multiplied with the DBT image. Secondly, an efficient U-Net neural network is built and image patches are extracted before data augmentation to establish the training dataset to train the U-Net model. ...
Source: Computational and Mathematical Methods in Medicine - May 17, 2020 Category: Statistics Tags: Comput Math Methods Med Source Type: research

Mathematical Prostate Cancer Evolution: Effect of Immunotherapy Based on Controlled Vaccination Strategy.
Authors: Ba Dziul D, Jakubczyk P, Chotorlishvili L, Toklikishvilie Z, Traciak J, Jakubowicz-Gil J, Chmiel-Szajner S Abstract Basic immunology research over several decades has led to an improved understanding of tumour recognition by components of the immune system and mechanism of tumour evasion from immune detection. These findings have ultimately led to creating antitumour immunotherapies in patients with different kind of cancer including prostate cancer. The increasing number of reports confirms that immune-based therapies have clinical benefit in patients with prostate cancer with potentially less toxicity in...
Source: Computational and Mathematical Methods in Medicine - May 17, 2020 Category: Statistics Tags: Comput Math Methods Med Source Type: research

Preoperative Evaluation of V-Y Flap Design Based on Computer-Aided Analysis.
Authors: Yang ZL, Peng YH, Yang C, Cheng B, Ji MK, Zhao Y Abstract V-Y flap is widely used in plastic surgery as an important technique for reconstructing deformities and improving appearance. In this paper, a geometrical parameter model and finite element analysis were used to study the rationale of the proposed V-Y flap design and the preoperative evaluation of the V-Y flap design. First, a geometric parameter model of the V-Y flap was established to analyze the five key geometric relationships affecting the flap structure and obtain a reasonable plan for the V-Y flap design through the crossing constraint relati...
Source: Computational and Mathematical Methods in Medicine - May 17, 2020 Category: Statistics Tags: Comput Math Methods Med Source Type: research

Ergodic Stationary Distribution of a Stochastic Hepatitis B Epidemic Model with Interval-Valued Parameters and Compensated Poisson Process.
Authors: Kiouach D, Sabbar Y Abstract Hepatitis B epidemic was and is still a rich subject that sparks the interest of epidemiological researchers. The dynamics of this epidemic is often modeled by a system with constant parameters. In reality, the parameters associated with the Hepatitis B model are not certain, but the interval in which it belongs to can readily be determined. Our paper focuses on an imprecise Hepatitis B model perturbed by Lévy noise due to unexpected environmental disturbances. This model has a global positive solution. Under an appropriate assumption, we prove the existence of a unique ...
Source: Computational and Mathematical Methods in Medicine - May 17, 2020 Category: Statistics Tags: Comput Math Methods Med Source Type: research

Identification of Pancreaticoduodenectomy Resection for Pancreatic Head Adenocarcinoma: A Preliminary Study of Radiomics.
Conclusions: It indicates that the radiomics study is rewarding for the aided diagnosis of R0 and R1. Texture features can potentially enhance physicians' diagnostic ability. PMID: 32377222 [PubMed - in process] (Source: Computational and Mathematical Methods in Medicine)
Source: Computational and Mathematical Methods in Medicine - May 8, 2020 Category: Statistics Tags: Comput Math Methods Med Source Type: research

In Silico Analysis Identifies Differently Expressed lncRNAs as Novel Biomarkers for the Prognosis of Thyroid Cancer.
Authors: Rao Y, Liu H, Yan X, Wang J Abstract Background: Thyroid cancer (TC) is one of the most common type of endocrine tumors. Long noncoding RNAs had been demonstrated to play key roles in TC. Material and Methods. The lncRNA expression data were downloaded from Co-lncRNA database. The raw data was normalized using the limma package in R software version 3.3.0. The differentially expressed mRNA and lncRNAs were identified by the linear models for the microarray analysis (Limma) method. The DEGs were obtained with thresholds of ∣logFC∣> 1.5 and P
Source: Computational and Mathematical Methods in Medicine - May 8, 2020 Category: Statistics Tags: Comput Math Methods Med Source Type: research

Examining Human Unipedal Quiet Stance: Characterizing Control through Jerk.
Authors: Semak MR, Schwartz J, Heise G Abstract We investigated the quality of smoothness during human unipedal quiet stance. Smoothness is quantified by the time rate of change of the accelerations, or jerks, associated with the motion of the foot and can be seen as an indicative of how controlled the balance process is. To become more acquainted with this as a quantity, we wanted to establish whether or not it can be modeled as a (stationary) stochastic process and, if so, explore its temporal scaling behavior. Specifically, our study focused on the jerk concerning the center-of-pressure (COP) for each foot. Data...
Source: Computational and Mathematical Methods in Medicine - May 8, 2020 Category: Statistics Tags: Comput Math Methods Med Source Type: research

Assessment of Lumbar Lordosis Distribution with a Novel Mathematical Approach and Its Adaptation for Lumbar Intervertebral Disc Degeneration.
Conclusions: Spinalyze Software based on a novel mathematical approach provides a free, easy-to-use, reliable, and online measurement tool using standard MRIs to approximate the curvature of lumbar lordosis. The new reliable K% (digression percentage) is one single quantitative parameter to assess the local distribution of total lumbar lordosis. The results indicate that digression percentage (K%) may possibly be associated with the development of lumbar intervertebral disc degeneration. Further evaluation is needed to assess its behavior and advantage. PMID: 32377225 [PubMed - in process] (Source: Computational and Ma...
Source: Computational and Mathematical Methods in Medicine - May 8, 2020 Category: Statistics Tags: Comput Math Methods Med Source Type: research

A Review of Multimodal Medical Image Fusion Techniques.
Authors: Huang B, Yang F, Yin M, Mo X, Zhong C Abstract The medical image fusion is the process of coalescing multiple images from multiple imaging modalities to obtain a fused image with a large amount of information for increasing the clinical applicability of medical images. In this paper, we attempt to give an overview of multimodal medical image fusion methods, putting emphasis on the most recent advances in the domain based on (1) the current fusion methods, including based on deep learning, (2) imaging modalities of medical image fusion, and (3) performance analysis of medical image fusion on mainly data set...
Source: Computational and Mathematical Methods in Medicine - May 8, 2020 Category: Statistics Tags: Comput Math Methods Med Source Type: research