# Computational and Mathematical Methods in Medicine This is an RSS file. You can use it to subscribe to this data in your favourite RSS reader or to display this data on your own website or blog.

**Hemoglobin-Dilution Method: Effect of Measurement Errors on Vascular Volume Estimation.**

This study uses a "Monte Carlo" approach to determine the distribution of these errors. The finding was that these errors could be closely approximated with a log-normal distribution that can be parameterized by a geometric mean (X) and a dispersion factor (S). When the ratio of successive Hb concentrations is used to estimate blood volume, normally distributed hemoglobin measurement errors tend to produce exponentially higher values of X and S as the SD of the measurement error increases. The longer tail of the distribution to the right could produce much greater overestimations than would be expected from the S...

**Source: **Computational and Mathematical Methods in Medicine - November 10, 2017 **Category: **Statistics **Tags: **Comput Math Methods Med **Source Type: **research

**Modelling Risk to US Military Populations from Stopping Blanket Mandatory Polio Vaccination.**

Conclusion: Risk-based immunization driven by deployment to polio-endemic regions is sufficient to prevent transmission among both deployed and nondeployed US military populations.
PMID: 29104608 [PubMed - in process] (Source: Computational and Mathematical Methods in Medicine)

**Source: **Computational and Mathematical Methods in Medicine - November 8, 2017 **Category: **Statistics **Tags: **Comput Math Methods Med **Source Type: **research

**Biomarker MicroRNAs for Diagnosis of Oral Squamous Cell Carcinoma Identified Based on Gene Expression Data and MicroRNA-mRNA Network Analysis.**

Authors: Zhang H, Li T, Zheng L, Huang X
Abstract
Oral squamous cell carcinoma is one of the most malignant tumors with high mortality rate worldwide. Biomarker discovery is critical for early diagnosis and precision treatment of this disease. MicroRNAs are small noncoding RNA molecules which often regulate essential biological processes and are good candidates for biomarkers. By integrative analysis of both the cancer-associated gene expression data and microRNA-mRNA network, miR-148b-3p, miR-629-3p, miR-27a-3p, and miR-142-3p were screened as novel diagnostic biomarkers for oral squamous cell carcinoma based on t...

**Source: **Computational and Mathematical Methods in Medicine - November 5, 2017 **Category: **Statistics **Tags: **Comput Math Methods Med **Source Type: **research

**Predictive Modelling Based on Statistical Learning in Biomedicine.**

Authors: Gefeller O, Hofner B, Mayr A, Waldmann E
PMID: 29093744 [PubMed - in process] (Source: Computational and Mathematical Methods in Medicine)

**Source: **Computational and Mathematical Methods in Medicine - November 3, 2017 **Category: **Statistics **Tags: **Comput Math Methods Med **Source Type: **research

**Modelling and Optimal Control of Typhoid Fever Disease with Cost-Effective Strategies.**

Authors: Tilahun GT, Makinde OD, Malonza D
Abstract
We propose and analyze a compartmental nonlinear deterministic mathematical model for the typhoid fever outbreak and optimal control strategies in a community with varying population. The model is studied qualitatively using stability theory of differential equations and the basic reproductive number that represents the epidemic indicator is obtained from the largest eigenvalue of the next-generation matrix. Both local and global asymptotic stability conditions for disease-free and endemic equilibria are determined. The model exhibits a forward transcritical bifur...

**Source: **Computational and Mathematical Methods in Medicine - October 31, 2017 **Category: **Statistics **Tags: **Comput Math Methods Med **Source Type: **research

**The Applications of Finite Element Analysis in Proximal Humeral Fractures.**

Authors: Ye Y, You W, Zhu W, Cui J, Chen K, Wang D
Abstract
Proximal humeral fractures are common and most challenging, due to the complexity of the glenohumeral joint, especially in the geriatric population with impacted fractures, that the development of implants continues because currently the problems with their fixation are not solved. Pre-, intra-, and postoperative assessments are crucial in management of those patients. Finite element analysis, as one of the valuable tools, has been implemented as an effective and noninvasive method to analyze proximal humeral fractures, providing solid evidence for managem...

**Source: **Computational and Mathematical Methods in Medicine - October 31, 2017 **Category: **Statistics **Tags: **Comput Math Methods Med **Source Type: **research

**Anisotropy Influences on the Drug Delivery Mechanisms by Means of Joint Invariant Functions.**

Authors: Cioca G, Bacaita ES, Agop M, Lupascu Ursulescu C
Abstract
In the frame of Higuchi's type functionality, this paper presents the anisotropy influences on the drug delivery mechanisms through the joint invariant functions to the simultaneous actions of the two SL(2R) isomorphic groups. Then, a new equation for drug delivery mechanism, independent of the type of polymer matrix and/or drug, is proposed.
PMID: 29081830 [PubMed - in process] (Source: Computational and Mathematical Methods in Medicine)

**Source: **Computational and Mathematical Methods in Medicine - October 31, 2017 **Category: **Statistics **Tags: **Comput Math Methods Med **Source Type: **research

**Stochastic Models of Emerging Infectious Disease Transmission on Adaptive Random Networks.**

We presented adaptive random network models to describe human behavioral change during epidemics and performed stochastic simulations of SIR (susceptible-infectious-recovered) epidemic models on adaptive random networks. The interplay between infectious disease dynamics and network adaptation dynamics was investigated in regard to the disease transmission and the cumulative number of infection cases. We found that the cumulative case was reduced and associated with an increasing network adaptation probability but was increased with an increasing disease transmission probability. It was found that the topological changes of...

**Source: **Computational and Mathematical Methods in Medicine - October 29, 2017 **Category: **Statistics **Tags: **Comput Math Methods Med **Source Type: **research

**Pathway Interaction Network Analysis Identifies Dysregulated Pathways in Human Monocytes Infected by Listeria monocytogenes.**

Authors: Fan W, Zhou Y, Li H
Abstract
In our study, we aimed to extract dysregulated pathways in human monocytes infected by Listeria monocytogenes (LM) based on pathway interaction network (PIN) which presented the functional dependency between pathways. After genes were aligned to the pathways, principal component analysis (PCA) was used to calculate the pathway activity for each pathway, followed by detecting seed pathway. A PIN was constructed based on gene expression profile, protein-protein interactions (PPIs), and cellular pathways. Identifying dysregulated pathways from the PIN was performed relying on seed...

**Source: **Computational and Mathematical Methods in Medicine - September 29, 2017 **Category: **Statistics **Tags: **Comput Math Methods Med **Source Type: **research

**Hamiltonian Analysis of Subcritical Stochastic Epidemic Dynamics.**

Authors: Worden L, Schwartz IB, Bianco S, Ackley SF, Lietman TM, Porco TC
Abstract
We extend a technique of approximation of the long-term behavior of a supercritical stochastic epidemic model, using the WKB approximation and a Hamiltonian phase space, to the subcritical case. The limiting behavior of the model and approximation are qualitatively different in the subcritical case, requiring a novel analysis of the limiting behavior of the Hamiltonian system away from its deterministic subsystem. This yields a novel, general technique of approximation of the quasistationary distribution of stochastic epidemic and bi...

**Source: **Computational and Mathematical Methods in Medicine - September 23, 2017 **Category: **Statistics **Tags: **Comput Math Methods Med **Source Type: **research

**Effect of Rainfall for the Dynamical Transmission Model of the Dengue Disease in Thailand.**

Authors: Chanprasopchai P, Pongsumpun P, Tang IM
Abstract
The SEIR (Susceptible-Exposed-Infected-Recovered) model is used to describe the transmission of dengue virus. The main contribution is determining the role of the rainfall in Thailand in the model. The transmission of dengue disease is assumed to depend on the nature of the rainfall in Thailand. We analyze the dynamic transmission of dengue disease. The stability of the solution of the model is analyzed. It is investigated by using the Routh-Hurwitz criteria. We find two equilibrium states: a disease-free state and an endemic equilibrium state. The basic rep...

**Source: **Computational and Mathematical Methods in Medicine - September 22, 2017 **Category: **Statistics **Tags: **Comput Math Methods Med **Source Type: **research

**Mechanistic Model for Cancer Growth and Response to Chemotherapy.**

Authors: Simbawa E
Abstract
Cancer treatment has developed over the years; however not all patients respond to this treatment, and therefore further research is needed. In this paper, we employ mathematical modeling to understand the behavior of cancer and its interaction with therapy. We study a drug delivery and drug-cell interaction model along with cell proliferation. Due to the fact that cancer cells grow when there are enough nutrients and oxygen, proliferation can be a barrier against a response to therapy. To understand the effect of this factor, we perform numerical simulations of the model for different v...

**Source: **Computational and Mathematical Methods in Medicine - September 22, 2017 **Category: **Statistics **Tags: **Comput Math Methods Med **Source Type: **research

**Sensitivity Analysis of the Integral Quality Monitoring System ® Using Monte Carlo Simulation.**

Sensitivity Analysis of the Integral Quality Monitoring System® Using Monte Carlo Simulation.
Comput Math Methods Med. 2017;2017:7025281
Authors: Oderinde OM, du Plessis FCP
Abstract
The Integral Quality Monitoring (IQM) System is a real-time beam output verifying system that validates the integrity and accuracy of patient treatment plan (TP) data during radiation treatment. The purpose of this study was to evaluate the sensitivity of the IQM to errors in segment using EGSnrc/BEAMnrc Monte Carlo (MC) codes. Sensitivity analysis (SA) techniques were applied to study the significance of small alterat...

**Source: **Computational and Mathematical Methods in Medicine - September 22, 2017 **Category: **Statistics **Tags: **Comput Math Methods Med **Source Type: **research

**Segmentation of Left and Right Ventricles in Cardiac MRI Using Active Contours.**

Authors: Soomro S, Akram F, Munir A, Lee CH, Choi KN
Abstract
Segmentation of left and right ventricles plays a crucial role in quantitatively analyzing the global and regional information in the cardiac magnetic resonance imaging (MRI). In MRI, the intensity inhomogeneity and weak or blurred object boundaries are the problems, which makes it difficult for the intensity-based segmentation methods to properly delineate the regions of interests (ROI). In this paper, a hybrid signed pressure force function (SPF) is proposed, which yields both local and global image fitted differences in an additive fashion. A characte...

**Source: **Computational and Mathematical Methods in Medicine - September 22, 2017 **Category: **Statistics **Tags: **Comput Math Methods Med **Source Type: **research

**Dendritic Immunotherapy Improvement for an Optimal Control Murine Model.**

Authors: Rangel-Reyes JC, Chimal-Eguía JC, Castillo-Montiel E
Abstract
Therapeutic protocols in immunotherapy are usually proposed following the intuition and experience of the therapist. In order to deduce such protocols mathematical modeling, optimal control and simulations are used instead of the therapist's experience. Clinical efficacy of dendritic cell (DC) vaccines to cancer treatment is still unclear, since dendritic cells face several obstacles in the host environment, such as immunosuppression and poor transference to the lymph nodes reducing the vaccine effect. In view of that, we have created a m...

**Source: **Computational and Mathematical Methods in Medicine - September 17, 2017 **Category: **Statistics **Tags: **Comput Math Methods Med **Source Type: **research

**Products of Compartmental Models in Epidemiology.**

Authors: Worden L, Porco TC
Abstract
We show that many structured epidemic models may be described using a straightforward product structure in this paper. Such products, derived from products of directed graphs, may represent useful refinements including geographic and demographic structure, age structure, gender, risk groups, or immunity status. Extension to multistrain dynamics, that is, pathogen heterogeneity, is also shown to be feasible in this framework. Systematic use of such products may aid in model development and exploration, can yield insight, and could form the basis of a systematic approach to numeri...

**Source: **Computational and Mathematical Methods in Medicine - September 14, 2017 **Category: **Statistics **Tags: **Comput Math Methods Med **Source Type: **research

**Computational and Mathematical Methods to Estimate the Basic Reproduction Number and Final Size for Single-Stage and Multistage Progression Disease Models for Zika with Preventative Measures.**

We present new mathematical models that include the impact of using selected preventative measures such as insecticide treated nets (ITN) in controlling or ameliorating the spread of the Zika virus. For these models, we derive the basic reproduction number and sharp estimates for the final size relation. We first present a single-stage model which is later extended to a new multistage model for Zika that incorporates more realistic incubation stages for both the humans and vectors. For each of these models, we derive a basic reproduction number and a final size relation estimate. We observe that the basic reproduction numb...

**Source: **Computational and Mathematical Methods in Medicine - September 13, 2017 **Category: **Statistics **Tags: **Comput Math Methods Med **Source Type: **research

**A Novel Dynamic Model Describing the Spread of the MERS-CoV and the Expression of Dipeptidyl Peptidase 4.**

Authors: Tang S, Ma W, Bai P
Abstract
The Middle East respiratory syndrome (MERS) coronavirus, a newly identified pathogen, causes severe pneumonia in humans. MERS is caused by a coronavirus known as MERS-CoV, which attacks the respiratory system. The recently defined receptor for MERS-CoV, dipeptidyl peptidase 4 (DPP4), is generally expressed in endothelial and epithelial cells and has been shown to be present on cultured human nonciliated bronchiolar epithelium cells. In this paper, a class of novel four-dimensional dynamic model describing the infection of MERS-CoV is given, and then global stability of the equi...

**Source: **Computational and Mathematical Methods in Medicine - September 13, 2017 **Category: **Statistics **Tags: **Comput Math Methods Med **Source Type: **research

**Several Indicators of Critical Transitions for Complex Diseases Based on Stochastic Analysis.**

Authors: Wang G, Li Y, Zou X
Abstract
Many complex diseases (chronic disease onset, development and differentiation, self-assembly, etc.) are reminiscent of phase transitions in a dynamical system: quantitative changes accumulate largely unnoticed until a critical threshold is reached, which causes abrupt qualitative changes of the system. Understanding such nonlinear behaviors is critical to dissect the multiple genetic/environmental factors that together shape the genetic and physiological landscape underlying basic biological functions and to identify the key driving molecules. Based on stochastic differential e...

**Source: **Computational and Mathematical Methods in Medicine - August 25, 2017 **Category: **Statistics **Tags: **Comput Math Methods Med **Source Type: **research

**A Multicriteria Approach to Find Predictive and Sparse Models with Stable Feature Selection for High-Dimensional Data.**

Authors: Bommert A, Rahnenführer J, Lang M
Abstract
Finding a good predictive model for a high-dimensional data set can be challenging. For genetic data, it is not only important to find a model with high predictive accuracy, but it is also important that this model uses only few features and that the selection of these features is stable. This is because, in bioinformatics, the models are used not only for prediction but also for drawing biological conclusions which makes the interpretability and reliability of the model crucial. We suggest using three target criteria when fitting a predictive model to a high...

**Source: **Computational and Mathematical Methods in Medicine - August 25, 2017 **Category: **Statistics **Tags: **Comput Math Methods Med **Source Type: **research

**Integration of Multiple Genomic Data Sources in a Bayesian Cox Model for Variable Selection and Prediction.**

Authors: Treppmann T, Ickstadt K, Zucknick M
Abstract
Bayesian variable selection becomes more and more important in statistical analyses, in particular when performing variable selection in high dimensions. For survival time models and in the presence of genomic data, the state of the art is still quite unexploited. One of the more recent approaches suggests a Bayesian semiparametric proportional hazards model for right censored time-to-event data. We extend this model to directly include variable selection, based on a stochastic search procedure within a Markov chain Monte Carlo sampler for inference. This equips...

**Source: **Computational and Mathematical Methods in Medicine - August 24, 2017 **Category: **Statistics **Tags: **Comput Math Methods Med **Source Type: **research

**Probing for Sparse and Fast Variable Selection with Model-Based Boosting.**

We present a new variable selection method based on model-based gradient boosting and randomly permuted variables. Model-based boosting is a tool to fit a statistical model while performing variable selection at the same time. A drawback of the fitting lies in the need of multiple model fits on slightly altered data (e.g., cross-validation or bootstrap) to find the optimal number of boosting iterations and prevent overfitting. In our proposed approach, we augment the data set with randomly permuted versions of the true variables, so-called shadow variables, and stop the stepwise fitting as soon as such a variable would be ...

**Source: **Computational and Mathematical Methods in Medicine - August 24, 2017 **Category: **Statistics **Tags: **Comput Math Methods Med **Source Type: **research

**An Update on Statistical Boosting in Biomedicine.**

Authors: Mayr A, Hofner B, Waldmann E, Hepp T, Meyer S, Gefeller O
Abstract
Statistical boosting algorithms have triggered a lot of research during the last decade. They combine a powerful machine learning approach with classical statistical modelling, offering various practical advantages like automated variable selection and implicit regularization of effect estimates. They are extremely flexible, as the underlying base-learners (regression functions defining the type of effect for the explanatory variables) can be combined with any kind of loss function (target function to be optimized, defining the type of regr...

**Source: **Computational and Mathematical Methods in Medicine - August 24, 2017 **Category: **Statistics **Tags: **Comput Math Methods Med **Source Type: **research

**A Multiscale Model for the World's First Parasitic Disease Targeted for Eradication: Guinea Worm Disease.**

Authors: Netshikweta R, Garira W
Abstract
Guinea worm disease (GWD) is both a neglected tropical disease and an environmentally driven infectious disease. Environmentally driven infectious diseases remain one of the biggest health threats for human welfare in developing countries and the threat is increased by the looming danger of climate change. In this paper we present a multiscale model of GWD that integrates the within-host scale and the between-host scale. The model is used to concurrently examine the interactions between the three organisms that are implicated in natural cases of GWD transmission, the copepo...

**Source: **Computational and Mathematical Methods in Medicine - August 18, 2017 **Category: **Statistics **Tags: **Comput Math Methods Med **Source Type: **research

**NSiteMatch: Prediction of Binding Sites of Nucleotides by Identifying the Structure Similarity of Local Surface Patches.**

In this study, we propose a nucleotide-binding site predictor, namely, NSiteMatch. The NSiteMatch algorithm integrates three different strategies: geometrical analysis, energy calculation, and template comparison. Unlike a traditional template-based predictor, which identifies global similarity between target structure and template, NSiteMatch concerns the local similarity between a surface patch of the target protein and the binding sites of template. To this end, NSiteMatch identifies more templates than traditional template-based predictors. The NSiteMatch predictor is compared with three representative methods, Findsit...

**Source: **Computational and Mathematical Methods in Medicine - August 18, 2017 **Category: **Statistics **Tags: **Comput Math Methods Med **Source Type: **research

**Convolutional Neural Network for the Detection of End-Diastole and End-Systole Frames in Free-Breathing Cardiac Magnetic Resonance Imaging.**

Authors: Yang F, He Y, Hussain M, Xie H, Lei P
Abstract
Free-breathing cardiac magnetic resonance (CMR) imaging has short examination time with high reproducibility. Detection of the end-diastole and the end-systole frames of the free-breathing cardiac magnetic resonance, supplemented by visual identification, is time consuming and laborious. We propose a novel method for automatic identification of both the end-diastole and the end-systole frames, in the free-breathing CMR imaging. The proposed technique utilizes the convolutional neural network to locate the left ventricle and to obtain the end-diastole and the e...

**Source: **Computational and Mathematical Methods in Medicine - August 18, 2017 **Category: **Statistics **Tags: **Comput Math Methods Med **Source Type: **research

**Computational Paradigms for Mental Health.**

Authors: Cipresso P, Matic A, Lopez G, Serino S
PMID: 28814966 [PubMed - in process] (Source: Computational and Mathematical Methods in Medicine)

**Source: **Computational and Mathematical Methods in Medicine - August 18, 2017 **Category: **Statistics **Tags: **Comput Math Methods Med **Source Type: **research

**Kalman Filtering for Genetic Regulatory Networks with Missing Values.**

Authors: Lin Q, Liu Q, Lai T, Wang W
Abstract
The filter problem with missing value for genetic regulation networks (GRNs) is addressed, in which the noises exist in both the state dynamics and measurement equations; furthermore, the correlation between process noise and measurement noise is also taken into consideration. In order to deal with the filter problem, a class of discrete-time GRNs with missing value, noise correlation, and time delays is established. Then a new observation model is proposed to decrease the adverse effect caused by the missing value and to decouple the correlation between process noise a...

**Source: **Computational and Mathematical Methods in Medicine - August 18, 2017 **Category: **Statistics **Tags: **Comput Math Methods Med **Source Type: **research

**Improved k-t PCA Algorithm Using Artificial Sparsity in Dynamic MRI.**

Authors: Wang Y, Chen Z, Wang J, Yuan L, Xia L, Liu F
Abstract
The k-t principal component analysis (k-t PCA) is an effective approach for high spatiotemporal resolution dynamic magnetic resonance (MR) imaging. However, it suffers from larger residual aliasing artifacts and noise amplification when the reduction factor goes higher. To further enhance the performance of this technique, we propose a new method called sparse k-t PCA that combines the k-t PCA algorithm with an artificial sparsity constraint. It is a self-calibrated procedure that is based on the traditional k-t PCA method by further eliminating the rec...

**Source: **Computational and Mathematical Methods in Medicine - August 15, 2017 **Category: **Statistics **Tags: **Comput Math Methods Med **Source Type: **research

**Altered Brain Functional Connectivity in Small-Cell Lung Cancer Patients after Chemotherapy Treatment: A Resting-State fMRI Study.**

Authors: Bromis K, Gkiatis K, Karanasiou I, Matsopoulos G, Karavasilis E, Papathanasiou M, Efstathopoulos E, Kelekis N, Kouloulias V
Abstract
Previous studies in small-cell lung cancer (SCLC) patients have mainly focused on exploring neurocognitive deficits associated with prophylactic cranial irradiation (PCI). Little is known about functional brain alterations that might occur due to chemotherapy treatment in this population before PCI is administered. For this reason, we used resting-state functional Magnetic Resonance Imaging (fMRI) to examine potential functional connectivity disruptions in brain networks, inc...

**Source: **Computational and Mathematical Methods in Medicine - August 13, 2017 **Category: **Statistics **Tags: **Comput Math Methods Med **Source Type: **research

**Pathway-Based Kernel Boosting for the Analysis of Genome-Wide Association Studies.**

Authors: Friedrichs S, Manitz J, Burger P, Amos CI, Risch A, Chang-Claude J, Wichmann HE, Kneib T, Bickeböller H, Hofner B
Abstract
The analysis of genome-wide association studies (GWAS) benefits from the investigation of biologically meaningful gene sets, such as gene-interaction networks (pathways). We propose an extension to a successful kernel-based pathway analysis approach by integrating kernel functions into a powerful algorithmic framework for variable selection, to enable investigation of multiple pathways simultaneously. We employ genetic similarity kernels from the logistic kernel machine test (LKMT...

**Source: **Computational and Mathematical Methods in Medicine - August 10, 2017 **Category: **Statistics **Tags: **Comput Math Methods Med **Source Type: **research

**Mathematical Modeling for Inherited Diseases.**

Authors: Anis S, Khan M, Khan S
Abstract
We introduced a new nonassociative algebra, namely, left almost algebra, and discussed some of its genetic properties. We discussed the relation of this algebra with flexible algebra, Jordan algebra, and generalized Jordan algebra.
PMID: 28781606 [PubMed - in process] (Source: Computational and Mathematical Methods in Medicine)

**Source: **Computational and Mathematical Methods in Medicine - August 8, 2017 **Category: **Statistics **Tags: **Comput Math Methods Med **Source Type: **research

**A Monte Carlo Study of the Photon Spectrum due to the Different Materials Used in the Construction of Flattening Filters of LINAC.**

Authors: Jiménez JSE, Lagos MD, Martinez-Ovalle SA
Abstract
Different types the spectrum of photons were studied; they were emitted from the flattening filter of a LINAC Varian 2100 C/D that operates at 15 MV. The simplified geometry of the LINAC head was calculated using the MCNPX code based on the studies of the materials of the flattening filter, namely, SST, W, Pb, Fe, Ta, Al, and Cu. These materials were replaced in the flattening filter to calculate the photon spectra at the output of this device to obtain the spectrum that makes an impact with the patient. The different spectra obtained were an...

**Source: **Computational and Mathematical Methods in Medicine - August 5, 2017 **Category: **Statistics **Tags: **Comput Math Methods Med **Source Type: **research

**Threshold Dynamics of a Stochastic SIR Model with Vertical Transmission and Vaccination.**

Authors: Miao A, Zhang J, Zhang T, Pradeep BGSA
Abstract
A stochastic SIR model with vertical transmission and vaccination is proposed and investigated in this paper. The threshold dynamics are explored when the noise is small. The conditions for the extinction or persistence of infectious diseases are deduced. Our results show that large noise can lead to the extinction of infectious diseases which is conducive to epidemic diseases control.
PMID: 28761501 [PubMed - in process] (Source: Computational and Mathematical Methods in Medicine)

**Source: **Computational and Mathematical Methods in Medicine - August 3, 2017 **Category: **Statistics **Tags: **Comput Math Methods Med **Source Type: **research

**Corrigendum to "A Clinical Decision Support System for the Diagnosis, Fracture Risks and Treatment of Osteoporosis".**

Corrigendum to "A Clinical Decision Support System for the Diagnosis, Fracture Risks and Treatment of Osteoporosis".
Comput Math Methods Med. 2017;2017:5472789
Authors: Halldorsson BV, Bjornsson AH, Gudmundsson HT, Birgisson EO, Ludviksson BR, Gudbjornsson B
Abstract
[This corrects the article DOI: 10.1155/2015/189769.].
PMID: 28751924 [PubMed - in process] (Source: Computational and Mathematical Methods in Medicine)

**Source: **Computational and Mathematical Methods in Medicine - July 29, 2017 **Category: **Statistics **Tags: **Comput Math Methods Med **Source Type: **research

**Optimization of Classification Strategies of Acetowhite Temporal Patterns towards Improving Diagnostic Performance of Colposcopy.**

Authors: Gutiérrez-Fragoso K, Acosta-Mesa HG, Cruz-Ramírez N, Hernández-Jiménez R
Abstract
Efforts have been being made to improve the diagnostic performance of colposcopy, trying to help better diagnose cervical cancer, particularly in developing countries. However, improvements in a number of areas are still necessary, such as the time it takes to process the full digital image of the cervix, the performance of the computing systems used to identify different kinds of tissues, and biopsy sampling. In this paper, we explore three different, well-known automatic classification methods (k...

**Source: **Computational and Mathematical Methods in Medicine - July 28, 2017 **Category: **Statistics **Tags: **Comput Math Methods Med **Source Type: **research

**A Selective Ensemble Classification Method Combining Mammography Images with Ultrasound Images for Breast Cancer Diagnosis.**

Authors: Cong J, Wei B, He Y, Yin Y, Zheng Y
Abstract
Breast cancer has been one of the main diseases that threatens women's life. Early detection and diagnosis of breast cancer play an important role in reducing mortality of breast cancer. In this paper, we propose a selective ensemble method integrated with the KNN, SVM, and Naive Bayes to diagnose the breast cancer combining ultrasound images with mammography images. Our experimental results have shown that the selective classification method with an accuracy of 88.73% and sensitivity of 97.06% is efficient for breast cancer diagnosis. And indicator R presents a...

**Source: **Computational and Mathematical Methods in Medicine - July 26, 2017 **Category: **Statistics **Tags: **Comput Math Methods Med **Source Type: **research

**Mathematical Simulation of Transport Kinetics of Tumor-Imaging Radiopharmaceutical (99m)Tc-MIBI.**

Authors: Shevtsova ON, Shevtsova VK
Abstract
The proposed model describes in a quality way the process of tumor-imaging radiopharmaceutical (99m)Tc-MIBI distribution with taking into account radiopharmaceutical accumulation, elimination, and radioactive decay. The dependencies of concentration versus the time are analyzed. The model can be easily tested by the concentration data of the radioactive pharmaceuticals in the blood measured at early time point and late time point of the scanning, and the obtained data can be used for determination of the washout rate coefficient which is one of the existing oncology diag...

**Source: **Computational and Mathematical Methods in Medicine - July 15, 2017 **Category: **Statistics **Tags: **Comput Math Methods Med **Source Type: **research

**An Exercise Health Simulation Method Based on Integrated Human Thermophysiological Model.**

Authors: Jia N, Chen X, Yu L, Wang R, Yang K, Luo X
Abstract
Research of healthy exercise has garnered a keen research for the past few years. It is known that participation in a regular exercise program can help improve various aspects of cardiovascular function and reduce the risk of suffering from illness. But some exercise accidents like dehydration, exertional heatstroke, and even sudden death need to be brought to attention. If these exercise accidents can be analyzed and predicted before they happened, it will be beneficial to alleviate or avoid disease or mortality. To achieve this objective, an exercise he...

**Source: **Computational and Mathematical Methods in Medicine - July 15, 2017 **Category: **Statistics **Tags: **Comput Math Methods Med **Source Type: **research

**Automatic Detection of Epilepsy and Seizure Using Multiclass Sparse Extreme Learning Machine Classification.**

Authors: Wang Y, Li Z, Feng L, Zheng C, Zhang W
Abstract
An automatic detection system for distinguishing normal, ictal, and interictal electroencephalogram (EEG) signals is of great help in clinical practice. This paper presents a three-class classification system based on discrete wavelet transform (DWT) and the nonlinear sparse extreme learning machine (SELM) for epilepsy and epileptic seizure detection. Three-level lifting DWT using Daubechies order 4 wavelet is introduced to decompose EEG signals into delta, theta, alpha, and beta subbands. Considering classification accuracy and computational complexity, the ...

**Source: **Computational and Mathematical Methods in Medicine - July 15, 2017 **Category: **Statistics **Tags: **Comput Math Methods Med **Source Type: **research

**Sparse Representation Based Multi-Instance Learning for Breast Ultrasound Image Classification.**

Authors: Bing L, Wang W
Abstract
We propose a novel method based on sparse representation for breast ultrasound image classification under the framework of multi-instance learning (MIL). After image enhancement and segmentation, concentric circle is used to extract the global and local features for improving the accuracy in diagnosis and prediction. The classification problem of ultrasound image is converted to sparse representation based MIL problem. Each instance of a bag is represented as a sparse linear combination of all basis vectors in the dictionary, and then the bag is represented by one feature vector whi...

**Source: **Computational and Mathematical Methods in Medicine - July 12, 2017 **Category: **Statistics **Tags: **Comput Math Methods Med **Source Type: **research

**SIFT Based Vein Recognition Models: Analysis and Improvement.**

Authors: Wang G, Wang J
Abstract
Scale-Invariant Feature Transform (SIFT) is being investigated more and more to realize a less-constrained hand vein recognition system. Contrast enhancement (CE), compensating for deficient dynamic range aspects, is a must for SIFT based framework to improve the performance. However, evidence of negative influence on SIFT matching brought by CE is analysed by our experiments. We bring evidence that the number of extracted keypoints resulting by gradient based detectors increases greatly with different CE methods, while on the other hand the matching result of extracted invariant de...

**Source: **Computational and Mathematical Methods in Medicine - July 8, 2017 **Category: **Statistics **Tags: **Comput Math Methods Med **Source Type: **research

**Exponentially Modified Peak Functions in Biomedical Sciences and Related Disciplines.**

Authors: Golubev A
Abstract
In many cases relevant to biomedicine, a variable time, which features a certain distribution, is required for objects of interest to pass from an initial to an intermediate state, out of which they exit at random to a final state. In such cases, the distribution of variable times between exiting the initial and entering the final state must conform to the convolution of the first distribution and a negative exponential distribution. A common example is the exponentially modified Gaussian (EMG), which is widely used in chromatography for peak analysis and is long known as ex-Gaussian in ...

**Source: **Computational and Mathematical Methods in Medicine - July 6, 2017 **Category: **Statistics **Tags: **Comput Math Methods Med **Source Type: **research

**Analysis of Urine Flow in Three Different Ureter Models.**

In this study, we investigated urine flow in the abnormal situation. We made three different, curved tubular, funnel-shaped, and undulated ureter models that were based on human anatomy. A numerical analysis of the urine flow rate and pattern in the ureter was performed for a combination of the three different ureters, with and without a ureteral stenosis and with four different types of double J stents. The three ureters showed a difference in urine flow rate and pattern. Luminal flow rate was affected by ureter shape. The side holes of a double J stent played a different role in detour, which depended on ureter geometry....

**Source: **Computational and Mathematical Methods in Medicine - July 1, 2017 **Category: **Statistics **Tags: **Comput Math Methods Med **Source Type: **research

**A Feasibility Study of Geometric-Decomposition Coil Compression in MRI Radial Acquisitions.**

Authors: Wang J, Chen Z, Wang Y, Yuan L, Xia L
Abstract
Receiver arrays with a large number of coil elements are becoming progressively available because of their increased signal-to-noise ratio (SNR) and enhanced parallel imaging performance. However, longer reconstruction time and intensive computational cost have become significant concerns as the number of channels increases, especially in some iterative reconstructions. Coil compression can effectively solve this problem by linearly combining the raw data from multiple coils into fewer virtual coils. In this work, geometric-decomposition coil compression (GCC)...

**Source: **Computational and Mathematical Methods in Medicine - July 1, 2017 **Category: **Statistics **Tags: **Comput Math Methods Med **Source Type: **research

**Finding Solvable Units of Variables in Nonlinear ODEs of ECM Degradation Pathway Network.**

Authors: Kawasaki S, Minerva D, Itano K, Suzuki T
Abstract
We consider ordinary differential equation (ODE) model for a pathway network that arises in extracellular matrix (ECM) degradation. For solving the ODEs, we propose applying the mass conservation law (MCL), together with a stoichiometry called doubling rule, to them. Then it leads to extracting new units of variables in the ODEs that can be solved explicitly, at least in principle. The simulation results for the ODE solutions show that the numerical solutions are indeed in good accord with theoretical solutions and satisfy the MALs.
PMID: 28638440 [PubM...

**Source: **Computational and Mathematical Methods in Medicine - June 25, 2017 **Category: **Statistics **Tags: **Comput Math Methods Med **Source Type: **research

**Defining an Optimal Cut-Point Value in ROC Analysis: An Alternative Approach.**

In this study, a new approach, alternative to these methods, is proposed. The proposed approach is based on the value of the area under the ROC curve. This method defines the optimal cut-point value as the value whose sensitivity and specificity are the closest to the value of the area under the ROC curve and the absolute value of the difference between the sensitivity and specificity values is minimum. This approach is very practical. In this study, the results of the proposed method are compared with those of the standard approaches, by using simulated data with different distribution and homogeneity conditions as well a...

**Source: **Computational and Mathematical Methods in Medicine - June 25, 2017 **Category: **Statistics **Tags: **Comput Math Methods Med **Source Type: **research

**Weighted Polynomial Approximation for Automated Detection of Inspiratory Flow Limitation.**

This study involved investigating a real-time algorithm for detecting IFL during sleep. Three categories of inspiratory flow shape were collected from previous studies for use as a development set. Of these, 16 cases were labeled as non-IFL and 78 as IFL which were further categorized into minor level (20 cases) and severe level (58 cases) of obstruction. In this study, algorithms using polynomial functions were proposed for extracting the features of IFL. Methods using first- to third-order polynomial approximations were applied to calculate the fitting curve to obtain the mean absolute error. The proposed algorithm is de...

**Source: **Computational and Mathematical Methods in Medicine - June 22, 2017 **Category: **Statistics **Tags: **Comput Math Methods Med **Source Type: **research

**Inference of Biochemical S-Systems via Mixed-Variable Multiobjective Evolutionary Optimization.**

Authors: Chen Y, Chen D, Zou X
Abstract
Inference of the biochemical systems (BSs) via experimental data is important for understanding how biochemical components in vivo interact with each other. However, it is not a trivial task because BSs usually function with complex and nonlinear dynamics. As a popular ordinary equation (ODE) model, the S-System describes the dynamical properties of BSs by incorporating the power rule of biochemical reactions but behaves as a challenge because it has a lot of parameters to be confirmed. This work is dedicated to proposing a general method for inference of S-Systems by experim...

**Source: **Computational and Mathematical Methods in Medicine - June 15, 2017 **Category: **Statistics **Tags: **Comput Math Methods Med **Source Type: **research

**The Preventive Control of Zoonotic Visceral Leishmaniasis: Efficacy and Economic Evaluation.**

Authors: Shimozako HJ, Wu J, Massad E
Abstract
Zoonotic Visceral Leishmaniasis (ZVL) is one of the world's deadliest and neglected infectious diseases, according to World Health Organization. This disease is one of major human and veterinary medical significance. The sandfly and the reservoir in urban areas remain among the major challenges for the control activities. In this paper, we evaluated five control strategies (positive dog elimination, insecticide impregnated dog collar, dog vaccination, dog treatment, and sandfly population control), considering disease control results and cost-effectiveness. We elaborat...

**Source: **Computational and Mathematical Methods in Medicine - June 9, 2017 **Category: **Statistics **Tags: **Comput Math Methods Med **Source Type: **research