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Computational and Mathematical Methods in Medicine

Ilker Unal
ROC curve analysis is often applied to measure the diagnostic accuracy of a biomarker. The analysis results in two gains: diagnostic accuracy of the biomarker and the optimal cut-point value. There are many methods proposed in the literature to obtain the optimal cut-point value. 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...
2017: Computational and Mathematical Methods in Medicine
Shuji Kawasaki, Dhisa Minerva, Keiko Itano, Takashi Suzuki
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...
2017: Computational and Mathematical Methods in Medicine
Sheng-Cheng Huang, Hao-Yu Jan, Tieh-Cheng Fu, Wen-Chen Lin, Geng-Hong Lin, Wen-Chi Lin, Cheng-Lun Tsai, Kang-Ping Lin
Inspiratory flow limitation (IFL) is a critical symptom of sleep breathing disorders. A characteristic flattened flow-time curve indicates the presence of highest resistance 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...
2017: Computational and Mathematical Methods in Medicine
Ivan L Milankovic, Nikola V Mijailovic, Nenad D Filipovic, Aleksandar S Peulic
Image segmentation is one of the most common procedures in medical imaging applications. It is also a very important task in breast cancer detection. Breast cancer detection procedure based on mammography can be divided into several stages. The first stage is the extraction of the region of interest from a breast image, followed by the identification of suspicious mass regions, their classification, and comparison with the existing image database. It is often the case that already existing image databases have large sets of data whose processing requires a lot of time, and thus the acceleration of each of the processing stages in breast cancer detection is a very important issue...
2017: Computational and Mathematical Methods in Medicine
Frank Lam, Hsiang-Wei Lu, Chung-Che Wu, Zekeriya Aliyazicioglu, James S Kang
Clinical applications that require extraction and interpretation of physiological signals or waveforms are susceptible to corruption by noise or artifacts. Real-time hemodynamic monitoring systems are important for clinicians to assess the hemodynamic stability of surgical or intensive care patients by interpreting hemodynamic parameters generated by an analysis of aortic blood pressure (ABP) waveform measurements. Since hemodynamic parameter estimation algorithms often detect events and features from measured ABP waveforms to generate hemodynamic parameters, noise and artifacts integrated into ABP waveforms can severely distort the interpretation of hemodynamic parameters by hemodynamic algorithms...
2017: Computational and Mathematical Methods in Medicine
Armin Ott, Alexander Hapfelmeier
Two nonparametric methods for the identification of subgroups with outstanding outcome values are described and compared to each other in a simulation study and an application to clinical data. The Patient Rule Induction Method (PRIM) searches for box-shaped areas in the given data which exceed a minimal size and average outcome. This is achieved via a combination of iterative peeling and pasting steps, where small fractions of the data are removed or added to the current box. As an alternative, Classification and Regression Trees (CART) prediction models perform sequential binary splits of the data to produce subsets which can be interpreted as subgroups of heterogeneous outcome...
2017: Computational and Mathematical Methods in Medicine
Zhe Xiao, Yi Ding, Tian Lan, Cong Zhang, Chuanji Luo, Zhiguang Qin
We propose a novel classification framework to precisely identify individuals with Alzheimer's disease (AD) or mild cognitive impairment (MCI) from normal controls (NC). The proposed method combines three different features from structural MR images: gray-matter volume, gray-level cooccurrence matrix, and Gabor feature. These features can obtain both the 2D and 3D information of brains, and the experimental results show that a better performance can be achieved through the multifeature fusion. We also analyze the multifeatures combination correlation technologies and improve the SVM-RFE algorithm through the covariance method...
2017: Computational and Mathematical Methods in Medicine
Yu Chen, Dong Chen, Xiufen Zou
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 experimental data, using a biobjective optimization (BOO) model and a specially mixed-variable multiobjective evolutionary algorithm (mv-MOEA)...
2017: Computational and Mathematical Methods in Medicine
Helio Junji Shimozako, Jianhong Wu, Eduardo Massad
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...
2017: Computational and Mathematical Methods in Medicine
Nemanja Rajković, Bojana Krstonošić, Nebojša Milošević
This study calls attention to the difference between traditional box-counting method and its modification. The appropriate scaling factor, influence on image size and resolution, and image rotation, as well as different image presentation, are showed on the sample of asymmetrical neurons from the monkey dentate nucleus. The standard BC method and its modification were evaluated on the sample of 2D neuronal images from the human neostriatum. In addition, three box dimensions (which estimate the space-filling property, the shape, complexity, and the irregularity of dendritic tree) were used to evaluate differences in the morphology of type III aspiny neurons between two parts of the neostriatum...
2017: Computational and Mathematical Methods in Medicine
Farai Nyabadza, Lezanie Coetzee
The complex problem of drug abuse and drug-related crimes in communities in the Western Cape province cannot be studied in isolation but through the system they are embedded in. In this paper, a theoretical model to evaluate the syndemic of substance abuse and drug-related crimes within the Western Cape province of South Africa is constructed and explored. The dynamics of drug abuse and drug-related crimes within the Western Cape are simulated using STELLA software. The simulation results are consistent with the data from SACENDU and CrimeStats SA, highlighting the usefulness of such a model in designing and planning interventions to combat substance abuse and its related problems...
2017: Computational and Mathematical Methods in Medicine
Chuang-Kit Tey, Jinyoung An, Wan-Young Chung
Chronic obstructive pulmonary disease is a type of lung disease caused by chronically poor airflow that makes breathing difficult. As a chronic illness, it typically worsens over time. Therefore, pulmonary rehabilitation exercises and patient management for extensive periods of time are required. This paper presents a remote rehabilitation system for a multimodal sensors-based application for patients who have chronic breathing difficulties. The process involves the fusion of sensory data-captured motion data by stereo-camera and photoplethysmogram signal by a wearable PPG sensor-that are the input variables of a detection and evaluation framework...
2017: Computational and Mathematical Methods in Medicine
Yunfeng Wu, Pinnan Chen, Yuchen Yao, Xiaoquan Ye, Yugui Xiao, Lifang Liao, Meihong Wu, Jian Chen
Analysis of quantified voice patterns is useful in the detection and assessment of dysphonia and related phonation disorders. In this paper, we first study the linear correlations between 22 voice parameters of fundamental frequency variability, amplitude variations, and nonlinear measures. The highly correlated vocal parameters are combined by using the linear discriminant analysis method. Based on the probability density functions estimated by the Parzen-window technique, we propose an interclass probability risk (ICPR) method to select the vocal parameters with small ICPR values as dominant features and compare with the modified Kullback-Leibler divergence (MKLD) feature selection approach...
2017: Computational and Mathematical Methods in Medicine
Stefan Pollnow, Joachim Greiner, Tobias Oesterlein, Eike M Wülfers, Axel Loewe, Olaf Dössel
Radiofrequency ablation has become a first-line approach for curative therapy of many cardiac arrhythmias. Various existing catheter designs provide high spatial resolution to identify the best spot for performing ablation and to assess lesion formation. However, creation of transmural and nonconducting ablation lesions requires usage of catheters with larger electrodes and improved thermal conductivity, leading to reduced spatial sensitivity. As trade-off, an ablation catheter with integrated mini electrodes was introduced...
2017: Computational and Mathematical Methods in Medicine
Anne-Laure Boulesteix, Riccardo De Bin, Xiaoyu Jiang, Mathias Fuchs
As modern biotechnologies advance, it has become increasingly frequent that different modalities of high-dimensional molecular data (termed "omics" data in this paper), such as gene expression, methylation, and copy number, are collected from the same patient cohort to predict the clinical outcome. While prediction based on omics data has been widely studied in the last fifteen years, little has been done in the statistical literature on the integration of multiple omics modalities to select a subset of variables for prediction, which is a critical task in personalized medicine...
2017: Computational and Mathematical Methods in Medicine
José Alberto Benítez, José Emilio Labra, Enedina Quiroga, Vicente Martín, Isaías García, Pilar Marqués-Sánchez, Carmen Benavides
There is a great concern nowadays regarding alcohol consumption and drug abuse, especially in young people. Analyzing the social environment where these adolescents are immersed, as well as a series of measures determining the alcohol abuse risk or personal situation and perception using a number of questionnaires like AUDIT, FAS, KIDSCREEN, and others, it is possible to gain insight into the current situation of a given individual regarding his/her consumption behavior. But this analysis, in order to be achieved, requires the use of tools that can ease the process of questionnaire creation, data gathering, curation and representation, and later analysis and visualization to the user...
2017: Computational and Mathematical Methods in Medicine
Kengo Atomi, Haruki Kawanaka, Md Shoaib Bhuiyan, Koji Oguri
Measuring blood pressure continuously helps monitor health and also prevent lifestyle related diseases to extend the expectancy of healthy life. Blood pressure, which is nowadays used for monitoring patient, is one of the most useful indexes for prevention of lifestyle related diseases such as hypertension. However, continuously monitoring the blood pressure is unrealistic because of discomfort caused by the tightening of a cuff belt. We have earlier researched the data-oriented blood pressure estimation without using a cuff...
2017: Computational and Mathematical Methods in Medicine
Wei Zhou, Chengdong Wu, Dali Chen, Zhenzhu Wang, Yugen Yi, Wenyou Du
Red lesions can be regarded as one of the earliest lesions in diabetic retinopathy (DR) and automatic detection of red lesions plays a critical role in diabetic retinopathy diagnosis. In this paper, a novel superpixel Multichannel Multifeature (MCMF) classification approach is proposed for red lesion detection. In this paper, firstly, a new candidate extraction method based on superpixel is proposed. Then, these candidates are characterized by multichannel features, as well as the contextual feature. Next, FDA classifier is introduced to classify the red lesions among the candidates...
2017: Computational and Mathematical Methods in Medicine
SungHwan Kim, Jae-Hwan Jhong, JungJun Lee, Ja-Yong Koo, ByungYong Lee, SungWon Han
Up to date, many biological pathways related to cancer have been extensively applied thanks to outputs of burgeoning biomedical research. This leads to a new technical challenge of exploring and validating biological pathways that can characterize transcriptomic mechanisms across different disease subtypes. In pursuit of accommodating multiple studies, the joint Gaussian graphical model was previously proposed to incorporate nonzero edge effects. However, this model is inevitably dependent on post hoc analysis in order to confirm biological significance...
2017: Computational and Mathematical Methods in Medicine
Juana Canul-Reich, Juan Frausto-Solís, José Hernández-Torruco
Background. Guillain-Barré Syndrome (GBS) is a potentially fatal autoimmune neurological disorder. The severity varies among the four main subtypes, named as Acute Inflammatory Demyelinating Polyneuropathy (AIDP), Acute Motor Axonal Neuropathy (AMAN), Acute Motor Sensory Axonal Neuropathy (AMSAN), and Miller-Fisher Syndrome (MF). A proper subtype identification may help to promptly carry out adequate treatment in patients. Method. We perform experiments with 15 single classifiers in two scenarios: four subtypes' classification and One versus All (OvA) classification...
2017: Computational and Mathematical Methods in Medicine
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