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Computational and Mathematical Methods in Medicine

Li-Sheng Wei, Quan Gan, Tao Ji
Skin diseases have a serious impact on people's life and health. Current research proposes an efficient approach to identify singular type of skin diseases. It is necessary to develop automatic methods in order to increase the accuracy of diagnosis for multitype skin diseases. In this paper, three type skin diseases such as herpes, dermatitis, and psoriasis skin disease could be identified by a new recognition method. Initially, skin images were preprocessed to remove noise and irrelevant background by filtering and transformation...
2018: Computational and Mathematical Methods in Medicine
Jae Hun Jung, Anna Park, Il Hyo Jung
Recently, the role of the electronic cigarettes (e-cigarettes) in a way to reduce smoking is increasing. E-cigarettes are a device that delivers only the nicotine, and its use is considered less harmful to health compared with tobacco cigarettes. Smokers frequently make use of e-cigarettes as one of the nonsmoking aid devices. In this work, we propose a mathematical model to analyze the effect of e-cigarettes on smoking cessation. The stability and the bifurcation of the model have been discussed. The parameter estimations from the observed data are drawn, and using the parameters, a reasonable smoking model has been designed...
2018: Computational and Mathematical Methods in Medicine
Xiaoqing Wang, Dirk Voit, Volkert Roeloffs, Martin Uecker, Jens Frahm
Purpose: To develop a high-speed multislice T1 mapping method based on a single-shot inversion-recovery (IR) radial FLASH acquisition and a regularized model-based reconstruction. Methods: Multislice radial k-space data are continuously acquired after a single nonselective inversion pulse using a golden-angle sampling scheme in a spoke-interleaved manner with optimized flip angles. Parameter maps and coil sensitivities of each slice are estimated directly from highly undersampled radial k-space data using a model-based nonlinear inverse reconstruction in conjunction with joint sparsity constraints...
2018: Computational and Mathematical Methods in Medicine
Cynthia Kpekpena, Saman Muthukumarana
We consider a Bayesian approach for assessing hypotheses of equivalence in two-arm trials with binary Data. We discuss the development of likelihood, the prior, and the posterior distributions of parameters of interest. We then examine the suitability of a normal approximation to the posterior distribution obtained via a Taylor series expansion. The Bayesian inference is carried out using Markov Chain Monte Carlo (MCMC) methods. We illustrate the methods using actual data arising from two-arm clinical trials on preventing mortality after myocardial infarction...
2018: Computational and Mathematical Methods in Medicine
Rupert Faltermeier, Martin A Proescholdt, Stefan Wolf, Sylvia Bele, Alexander Brawanski
Recently, we introduced a mathematical toolkit called selected correlation analysis (sca) that reliably detects negative and positive correlations between arterial blood pressure (ABP) and intracranial pressure (ICP) data, recorded during multimodal monitoring, in a time-resolved way. As has been shown with the aid of a mathematical model of cerebral perfusion, such correlations reflect impaired autoregulation and reduced intracranial compliance in patients with critical neurological diseases. Sca calculates a Fourier transform-based index called selected correlation (sc) that reflects the strength of correlation between the input data and simultaneously an index called mean Hilbert phase difference (mhpd) that reflects the phasing between the data...
2018: Computational and Mathematical Methods in Medicine
YuXiu Meng, Xue Hong Cai, LiPei Wang
Background: Neonatal sepsis (NS) is considered as the most common cause of neonatal deaths that newborns suffer from. Although numerous studies focus on gene biomarkers of NS, the predictive value of the gene biomarkers is low. NS pathogenesis is still needed to be investigated. Methods: After data preprocessing, we used KEGG enrichment method to identify the differentially expressed pathways between NS and normal controls. Then, functional principal component analysis (FPCA) was adopted to calculate gene values in NS...
2018: Computational and Mathematical Methods in Medicine
Alessandra Paffi, Francesca Camera, Chiara Carocci, Francesca Apollonio, Micaela Liberti
Tinnitus is a debilitating perception of sound in the absence of external auditory stimuli. It may have either a central or a peripheral origin in the cochlea. Experimental studies evidenced that an electrical stimulation of peripheral auditory fibers may alleviate symptoms but the underlying mechanisms are still unknown. In this work, a stochastic neuron model is used, that mimics an auditory fiber affected by tinnitus, to check the effects, in terms of firing reduction, of different kinds of electric stimulations, i...
2018: Computational and Mathematical Methods in Medicine
Shuiping Gou, Linlin Chen, Yu Gu, Liyu Huang, Meiping Huang, Jian Zhuang
The surgical treatment of congenital heart disease requires navigational assistance with transesophageal echocardiography (TEE); however, TEE images are often difficult to interpret and provide very limited anatomical information. Registering preoperative CT images to intraoperative TEE images provides surgeons with richer and more useful anatomical information. Yet, CT and TEE images differ substantially in terms of scale and geometry. In the present research, we propose a novel method for the registration of CT and TEE images for navigation during surgical repair of large defects in patients with congenital heart disease...
2018: Computational and Mathematical Methods in Medicine
Xiaoyun Wang, Min Zhao, Xiaoqiang Wang, Shuping Li, Ning Cao, Huirong Liu
High titer of β 1 -adrenoreceptor autoantibodies ( β 1 -AA) has been reported to appear in heart failure patients. It induces sustained β 1 -adrenergic receptor ( β 1 -AR) activation which leads to heart failure (HF), but the mechanism is as yet unclear. In order to investigate the mechanisms causing β 1 -AR non-desensitization, we studied the beating frequency of the neonatal rat cardiomyocytes (NRCMs) under different conditions (an injection of isoprenaline (ISO) for one group and β 1 -AA for the other) and established three dynamic models in order to best describe the true relationships shown in medical experiments; one model used a control group of healthy rats; then in HF rats one focused on conformation changes in β 1 -AR; the other examined interaction between β 1 -AR and β 2 -adrenergic receptors ( β 2 -AR)...
2018: Computational and Mathematical Methods in Medicine
Innokentiy Kastalskiy, Vasily Mironov, Sergey Lobov, Nadia Krilova, Alexey Pimashkin, Victor Kazantsev
A neuromuscular interface (NI) that can be employed to operate external robotic devices (RD), including commercial ones, was proposed. Multichannel electromyographic (EMG) signal is used in the control loop. Control signal can also be supplemented with electroencephalography (EEG), limb kinematics, or other modalities. The multiple electrode approach takes advantage of the massive resources of the human brain for solving nontrivial tasks, such as movement coordination. Multilayer artificial neural network was used for feature classification and further to provide command and/or proportional control of three robotic devices...
2018: Computational and Mathematical Methods in Medicine
Sanghun Choi, Shinjiro Miyawaki, Ching-Long Lin
This study aims to investigate the effect of altered structures and functions in severe asthma on particle deposition by using computational fluid dynamics (CFD) models. Airway geometrical models of two healthy subjects and two severe asthmatics were reconstructed from computed tomography (CT) images. Subject-specific flow boundary conditions were obtained by image registration to account for regional functional alterations of severe asthmatics. A large eddy simulation (LES) model for transitional and turbulent flows was applied to simulate airflows, and particle transport simulations were then performed for 2...
2018: Computational and Mathematical Methods in Medicine
Atta-Ur-Rahman, Kiran Sultan, Nahier Aldhafferi, Abdullah Alqahtani, Maqsood Mahmud
A novel reversible digital watermarking technique for medical images to achieve high level of secrecy, tamper detection, and blind recovery of the original image is proposed. The technique selects some of the pixels from the host image using chaotic key for embedding a chaotically generated watermark. The rest of the pixels are converted to residues by using the Residue Number System (RNS). The chaotically selected pixels are represented by the polynomial. A primitive polynomial of degree four is chosen that divides the message polynomial and consequently the remainder is obtained...
2018: Computational and Mathematical Methods in Medicine
Aytuğ Onan
Text mining is an important research direction, which involves several fields, such as information retrieval, information extraction, and text categorization. In this paper, we propose an efficient multiple classifier approach to text categorization based on swarm-optimized topic modelling. The Latent Dirichlet allocation (LDA) can overcome the high dimensionality problem of vector space model, but identifying appropriate parameter values is critical to performance of LDA. Swarm-optimized approach estimates the parameters of LDA, including the number of topics and all the other parameters involved in LDA...
2018: Computational and Mathematical Methods in Medicine
Yukai Li, Huling Li, Hua Yao
The focus of this study is the use of machine learning methods that combine feature selection and imbalanced process (SMOTE algorithm) to classify and predict diabetes follow-up control satisfaction data. After the feature selection and unbalanced process, diabetes follow-up data of the New Urban Area of Urumqi, Xinjiang, was used as input variables of support vector machine (SVM), decision tree, and integrated learning model (Adaboost and Bagging) for modeling and prediction. The experimental results show that Adaboost algorithm produces better classification results...
2018: Computational and Mathematical Methods in Medicine
J C A Dias, L H A Monteiro
Here, the propagation of vector-borne diseases is modeled by using a probabilistic cellular automaton. Numerical simulations considering distinct spatial distributions and time variations of the vector abundance are performed, in order to investigate their impacts on the number of infected individuals of the host population. The main conclusion is as follows: in the clustered distributions, the prevalence is lower, but the eradication is more difficult to be achieved, as compared to homogeneous distributions...
2018: Computational and Mathematical Methods in Medicine
Leonid Shaikhet, Svetlana Bunimovich-Mendrazitsky
We present a revised mathematical model of the immune response to Bacillus Calmette-Guérin (BCG) treatment of bladder cancer, optimized according to biological and clinical data accumulated during the last decade. The improved model accounts for cytotoxic T lymphocyte differentiation as an integral element of the delayed immune response, as well as the logistic growth terms for cancer cell proliferation. Three equilibria are demonstrated for the proposed model, which is assumed to be influenced by white noise stochastic perturbations that are directly proportional to the system state deviation from an equilibrium...
2018: Computational and Mathematical Methods in Medicine
Jinhyuk Kim, David Marcusson-Clavertz, Fumiharu Togo, Hyuntae Park
There is growing interest in within-person associations of objectively measured physical and physiological variables with psychological states in daily life. Here we provide a practical guide with SAS code of multilevel modeling for analyzing physical activity data obtained by accelerometer and self-report data from intensive and repeated measures using ecological momentary assessments (EMA). We review previous applications of EMA in research and clinical settings and the analytical tools that are useful for EMA research...
2018: Computational and Mathematical Methods in Medicine
Hongwu Tan, Hui Cao
We build and study the transmission dynamics of a hand-foot-mouth disease model with vaccination. The reproduction number is given, the existence of equilibria is obtained, and the global stability of disease-free equilibrium is proved by constructing the Lyapunov function. We also apply optimal control theory to the hand-foot-mouth disease model. The treatment and vaccination interventions are considered in the hand-foot-mouth disease model, and the optimal control strategies based on minimizing the cost of intervention and minimizing the number of the infected people are given...
2018: Computational and Mathematical Methods in Medicine
Marcos Amaku, Francisco Antonio Bezerra Coutinho, Margaret Armstrong, Eduardo Massad
We present two probabilistic models to estimate the risk of introducing infectious diseases into previously unaffected countries/regions by infective travellers. We analyse two distinct situations, one dealing with a directly transmitted infection (measles in Italy in 2017) and one dealing with a vector-borne infection (Zika virus in Rio de Janeiro, which may happen in the future). To calculate the risk in the first scenario, we used a simple, nonhomogeneous birth process. The second model proposed in this paper provides a way to calculate the probability that local mosquitoes become infected by the arrival of a single infective traveller during his/her infectiousness period...
2018: Computational and Mathematical Methods in Medicine
Wenpeng Gao, Xiaoguang Chen, Yili Fu, Minwei Zhu
The centerline, as a simple and compact representation of object shape, has been used to analyze variations of the human callosal shape. However, automatic extraction of the callosal centerline remains a sophisticated problem. In this paper, we propose a method of automatic extraction of the callosal centerline from segmented mid-sagittal magnetic resonance (MR) images. A model-based point matching method is introduced to localize the anterior and posterior endpoints of the centerline. The model of the endpoint is constructed with a statistical descriptor of the shape context...
2018: Computational and Mathematical Methods in Medicine
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