A Staging Auxiliary Diagnosis Model for Nonsmall Cell Lung Cancer Based on the Intelligent Medical System
This article is based on the data of 8,920 nonsmall cell lung cancer patients collected by different medical systems in three hospitals in China. Based on the intelligent medical system, on the basis of the intelligent medical system, this paper constructs a nonsmall cell lung cancer staging auxiliary diagnosis model based on convolutional neural network (CNNSAD). CNNSAD converts patient medical records into word sequences, uses convolutional neural networks to extract semantic features from patient medical records, and combines dynamic sampling and transfer learning technology to construct a balanced data set. The experim...
Source: Computational and Mathematical Methods in Medicine - February 25, 2021 Category: Statistics Authors: Jia Wu Fangfang Gou Yanlin Tan Source Type: research

Associating Multivariate Traits with Genetic Variants Using Collapsing and Kernel Methods with Pedigree- or Population-Based Studies
Comput Math Methods Med. 2021 Feb 9;2021:8812282. doi: 10.1155/2021/8812282. eCollection 2021.ABSTRACTIn genetic association analysis, several relevant phenotypes or multivariate traits with different types of components are usually collected to study complex or multifactorial diseases. Over the past few years, jointly testing for association between multivariate traits and multiple genetic variants has become more popular because it can increase statistical power to identify causal genes in pedigree- or population-based studies. However, most of the existing methods mainly focus on testing genetic variants associated with...
Source: Computational and Mathematical Methods in Medicine - February 25, 2021 Category: Statistics Authors: Li-Chu Chien Source Type: research

A Staging Auxiliary Diagnosis Model for Nonsmall Cell Lung Cancer Based on the Intelligent Medical System
This article is based on the data of 8,920 nonsmall cell lung cancer patients collected by different medical systems in three hospitals in China. Based on the intelligent medical system, on the basis of the intelligent medical system, this paper constructs a nonsmall cell lung cancer staging auxiliary diagnosis model based on convolutional neural network (CNNSAD). CNNSAD converts patient medical records into word sequences, uses convolutional neural networks to extract semantic features from patient medical records, and combines dynamic sampling and transfer learning technology to construct a balanced data set. The experim...
Source: Computational and Mathematical Methods in Medicine - February 25, 2021 Category: Statistics Authors: Jia Wu Fangfang Gou Yanlin Tan Source Type: research

Associating Multivariate Traits with Genetic Variants Using Collapsing and Kernel Methods with Pedigree- or Population-Based Studies
Comput Math Methods Med. 2021 Feb 9;2021:8812282. doi: 10.1155/2021/8812282. eCollection 2021.ABSTRACTIn genetic association analysis, several relevant phenotypes or multivariate traits with different types of components are usually collected to study complex or multifactorial diseases. Over the past few years, jointly testing for association between multivariate traits and multiple genetic variants has become more popular because it can increase statistical power to identify causal genes in pedigree- or population-based studies. However, most of the existing methods mainly focus on testing genetic variants associated with...
Source: Computational and Mathematical Methods in Medicine - February 25, 2021 Category: Statistics Authors: Li-Chu Chien Source Type: research

A Staging Auxiliary Diagnosis Model for Nonsmall Cell Lung Cancer Based on the Intelligent Medical System
This article is based on the data of 8,920 nonsmall cell lung cancer patients collected by different medical systems in three hospitals in China. Based on the intelligent medical system, on the basis of the intelligent medical system, this paper constructs a nonsmall cell lung cancer staging auxiliary diagnosis model based on convolutional neural network (CNNSAD). CNNSAD converts patient medical records into word sequences, uses convolutional neural networks to extract semantic features from patient medical records, and combines dynamic sampling and transfer learning technology to construct a balanced data set. The experim...
Source: Computational and Mathematical Methods in Medicine - February 25, 2021 Category: Statistics Authors: Jia Wu Fangfang Gou Yanlin Tan Source Type: research

Associating Multivariate Traits with Genetic Variants Using Collapsing and Kernel Methods with Pedigree- or Population-Based Studies
Comput Math Methods Med. 2021 Feb 9;2021:8812282. doi: 10.1155/2021/8812282. eCollection 2021.ABSTRACTIn genetic association analysis, several relevant phenotypes or multivariate traits with different types of components are usually collected to study complex or multifactorial diseases. Over the past few years, jointly testing for association between multivariate traits and multiple genetic variants has become more popular because it can increase statistical power to identify causal genes in pedigree- or population-based studies. However, most of the existing methods mainly focus on testing genetic variants associated with...
Source: Computational and Mathematical Methods in Medicine - February 25, 2021 Category: Statistics Authors: Li-Chu Chien Source Type: research

A Staging Auxiliary Diagnosis Model for Nonsmall Cell Lung Cancer Based on the Intelligent Medical System
This article is based on the data of 8,920 nonsmall cell lung cancer patients collected by different medical systems in three hospitals in China. Based on the intelligent medical system, on the basis of the intelligent medical system, this paper constructs a nonsmall cell lung cancer staging auxiliary diagnosis model based on convolutional neural network (CNNSAD). CNNSAD converts patient medical records into word sequences, uses convolutional neural networks to extract semantic features from patient medical records, and combines dynamic sampling and transfer learning technology to construct a balanced data set. The experim...
Source: Computational and Mathematical Methods in Medicine - February 25, 2021 Category: Statistics Authors: Jia Wu Fangfang Gou Yanlin Tan Source Type: research

Associating Multivariate Traits with Genetic Variants Using Collapsing and Kernel Methods with Pedigree- or Population-Based Studies
Comput Math Methods Med. 2021 Feb 9;2021:8812282. doi: 10.1155/2021/8812282. eCollection 2021.ABSTRACTIn genetic association analysis, several relevant phenotypes or multivariate traits with different types of components are usually collected to study complex or multifactorial diseases. Over the past few years, jointly testing for association between multivariate traits and multiple genetic variants has become more popular because it can increase statistical power to identify causal genes in pedigree- or population-based studies. However, most of the existing methods mainly focus on testing genetic variants associated with...
Source: Computational and Mathematical Methods in Medicine - February 25, 2021 Category: Statistics Authors: Li-Chu Chien Source Type: research

An ECG Signal Classification Method Based on Dilated Causal Convolution.
Authors: Ma H, Chen C, Zhu Q, Yuan H, Chen L, Shu M Abstract The incidence of cardiovascular disease is increasing year by year and is showing a younger trend. At the same time, existing medical resources are tight. The automatic detection of ECG signals becomes increasingly necessary. This paper proposes an automatic classification of ECG signals based on a dilated causal convolutional neural network. To solve the problem that the recurrent neural network framework network cannot be accelerated by hardware equipment, the dilated causal convolutional neural network is adopted. Given the features of the same input a...
Source: Computational and Mathematical Methods in Medicine - February 21, 2021 Category: Statistics Tags: Comput Math Methods Med Source Type: research

Decision Model for Allocation of Intensive Care Unit Beds for Suspected COVID-19 Patients under Scarce Resources.
Authors: Frej EA, Roselli LRP, Ferreira RJP, Alberti AR, de Almeida AT Abstract This paper puts forward a decision model for allocation of intensive care unit (ICU) beds under scarce resources in healthcare systems during the COVID-19 pandemic. The model is built upon a portfolio selection approach under the concepts of the Utility Theory. A binary integer optimization model is developed in order to find the best allocation for ICU beds, considering candidate patients with suspected/confirmed COVID-19. Experts' subjective knowledge and prior probabilities are considered to estimate the input data for the proposed m...
Source: Computational and Mathematical Methods in Medicine - February 13, 2021 Category: Statistics Tags: Comput Math Methods Med Source Type: research

Deep Learning-Based Acute Ischemic Stroke Lesion Segmentation Method on Multimodal MR Images Using a Few Fully Labeled Subjects.
Authors: Zhao B, Liu Z, Liu G, Cao C, Jin S, Wu H, Ding S Abstract Acute ischemic stroke (AIS) has been a common threat to human health and may lead to severe outcomes without proper and prompt treatment. To precisely diagnose AIS, it is of paramount importance to quantitatively evaluate the AIS lesions. By adopting a convolutional neural network (CNN), many automatic methods for ischemic stroke lesion segmentation on magnetic resonance imaging (MRI) have been proposed. However, most CNN-based methods should be trained on a large amount of fully labeled subjects, and the label annotation is a labor-intensive and ti...
Source: Computational and Mathematical Methods in Medicine - February 12, 2021 Category: Statistics Tags: Comput Math Methods Med Source Type: research

Reference-Driven Undersampled MR Image Reconstruction Using Wavelet Sparsity-Constrained Deep Image Prior.
Authors: Zhao D, Huang Y, Zhao F, Qin B, Zheng J Abstract Deep learning has shown potential in significantly improving performance for undersampled magnetic resonance (MR) image reconstruction. However, one challenge for the application of deep learning to clinical scenarios is the requirement of large, high-quality patient-based datasets for network training. In this paper, we propose a novel deep learning-based method for undersampled MR image reconstruction that does not require pre-training procedure and pre-training datasets. The proposed reference-driven method using wavelet sparsity-constrained deep image pr...
Source: Computational and Mathematical Methods in Medicine - February 9, 2021 Category: Statistics Tags: Comput Math Methods Med Source Type: research

Analyzing Surgical Treatment of Intestinal Obstruction in Children with Artificial Intelligence.
This study shows that the proposed algorithm has direct meaning to processing of clinical text data of childhood ileus. PMID: 33505514 [PubMed - in process] (Source: Computational and Mathematical Methods in Medicine)
Source: Computational and Mathematical Methods in Medicine - January 30, 2021 Category: Statistics Tags: Comput Math Methods Med Source Type: research

iBLP: An XGBoost-Based Predictor for Identifying Bioluminescent Proteins.
Authors: Zhang D, Chen HD, Zulfiqar H, Yuan SS, Huang QL, Zhang ZY, Deng KJ Abstract Bioluminescent proteins (BLPs) are a class of proteins that widely distributed in many living organisms with various mechanisms of light emission including bioluminescence and chemiluminescence from luminous organisms. Bioluminescence has been commonly used in various analytical research methods of cellular processes, such as gene expression analysis, drug discovery, cellular imaging, and toxicity determination. However, the identification of bioluminescent proteins is challenging as they share poor sequence similarities among them...
Source: Computational and Mathematical Methods in Medicine - January 30, 2021 Category: Statistics Tags: Comput Math Methods Med Source Type: research

iT3SE-PX: Identification of Bacterial Type III Secreted Effectors Using PSSM Profiles and XGBoost Feature Selection.
In this study, we proposed a method, called iT3SE-PX, to identify T3SEs solely based on protein sequences. First, three kinds of features were extracted from the position-specific scoring matrix (PSSM) profiles to help train a machine learning (ML) model. Then, the extreme gradient boosting (XGBoost) algorithm was performed to rank these features based on their classification ability. Finally, the optimal features were selected as inputs to a support vector machine (SVM) classifier to predict T3SEs. Based on the two benchmark datasets, we conducted a 100-time randomized 5-fold cross validation (CV) and an independent test,...
Source: Computational and Mathematical Methods in Medicine - January 30, 2021 Category: Statistics Tags: Comput Math Methods Med Source Type: research

Choroid Segmentation of Retinal OCT Images Based on CNN Classifier and l 2-l q Fitter.
Authors: He F, Chun RKM, Qiu Z, Yu S, Shi Y, To CH, Chen X Abstract Optical coherence tomography (OCT) is a noninvasive cross-sectional imaging technology used to examine the retinal structure and pathology of the eye. Evaluating the thickness of the choroid using OCT images is of great interests for clinicians and researchers to monitor the choroidal thickness in many ocular diseases for diagnosis and management. However, manual segmentation and thickness profiling of choroid are time-consuming which lead to low efficiency in analyzing a large quantity of OCT images for swift treatment of patients. In this paper, ...
Source: Computational and Mathematical Methods in Medicine - January 30, 2021 Category: Statistics Tags: Comput Math Methods Med Source Type: research

Effect-Size Estimation Using Semiparametric Hierarchical Mixture Models in Disease-Association Studies with Neuroimaging Data.
Authors: Emoto R, Kawaguchi A, Takahashi K, Matsui S Abstract In disease-association studies using neuroimaging data, evaluating the biological or clinical significance of individual associations requires not only detection of disease-associated areas of the brain but also estimation of the magnitudes of the associations or effect sizes for individual brain areas. In this paper, we propose a model-based framework for voxel-based inferences under spatial dependency in neuroimaging data. Specifically, we employ hierarchical mixture models with a hidden Markov random field structure to incorporate the spatial dependen...
Source: Computational and Mathematical Methods in Medicine - January 27, 2021 Category: Statistics Tags: Comput Math Methods Med Source Type: research

iPTT(2 ‚ÄČL)-CNN: A Two-Layer Predictor for Identifying Promoters and Their Types in Plant Genomes by Convolutional Neural Network.
iPTT(2 L)-CNN: A Two-Layer Predictor for Identifying Promoters and Their Types in Plant Genomes by Convolutional Neural Network. Comput Math Methods Med. 2021;2021:6636350 Authors: Sun A, Xiao X, Xu Z Abstract A promoter is a short DNA sequence near to the start codon, responsible for initiating transcription of a specific gene in genome. The accurate recognition of promoters has great significance for a better understanding of the transcriptional regulation. Because of their importance in the process of biological transcriptional regulation, there is an urgent need to develop in silico tools to...
Source: Computational and Mathematical Methods in Medicine - January 27, 2021 Category: Statistics Tags: Comput Math Methods Med Source Type: research

iMPTCE-Hnetwork: A Multilabel Classifier for Identifying Metabolic Pathway Types of Chemicals and Enzymes with a Heterogeneous Network.
In this study, we proposed a powerful multilabel classifier, called iMPTCE-Hnetwork, to uniformly assign chemicals and enzymes to metabolic pathway types reported in KEGG. Such classifier adopted the embedding features derived from a heterogeneous network, which defined chemicals and enzymes as nodes and the interactions between chemicals and enzymes as edges, through a powerful network embedding algorithm, Mashup. The popular RAndom k-labELsets (RAKEL) algorithm was employed to construct the classifier, which incorporated the support vector machine (polynomial kernel) as the basic classifier. The ten-fold cross-validation...
Source: Computational and Mathematical Methods in Medicine - January 27, 2021 Category: Statistics Tags: Comput Math Methods Med Source Type: research

Parameter Estimation and Prediction of COVID-19 Epidemic Turning Point and Ending Time of a Case Study on SIR/SQAIR Epidemic Models.
Authors: Amiri Mehra AH, Shafieirad M, Abbasi Z, Zamani I Abstract In this paper, the SIR epidemiological model for the COVID-19 with unknown parameters is considered in the first strategy. Three curves (S, I, and R) are fitted to the real data of South Korea, based on a detailed analysis of the actual data of South Korea, taken from the Korea Disease Control and Prevention Agency (KDCA). Using the least square method and minimizing the error between the fitted curve and the actual data, unknown parameters, like the transmission rate, recovery rate, and mortality rate, are estimated. The goodness of fit model is in...
Source: Computational and Mathematical Methods in Medicine - January 20, 2021 Category: Statistics Tags: Comput Math Methods Med Source Type: research

Prognostic Correlation of an Autophagy-Related Gene Signature in Patients with Head and Neck Squamous Cell Carcinoma.
In conclusion, this study provides a novel autophagy-related gene signature for predicting prognosis of HNSCC patients and gives molecular insights of autophagy in HNSCC. PMID: 33456497 [PubMed - in process] (Source: Computational and Mathematical Methods in Medicine)
Source: Computational and Mathematical Methods in Medicine - January 20, 2021 Category: Statistics Tags: Comput Math Methods Med Source Type: research

A Simple Cardiovascular Model for the Study of Hemorrhagic Shock.
Authors: Curcio L, D'Orsi L, Cibella F, Wagnert-Avraham L, Nachman D, De Gaetano A Abstract Hemorrhagic shock is the number one cause of death on the battlefield and in civilian trauma as well. Mathematical modeling has been applied in this context for decades; however, the formulation of a satisfactory model that is both practical and effective has yet to be achieved. This paper introduces an upgraded version of the 2007 Zenker model for hemorrhagic shock termed the ZenCur model that allows for a better description of the time course of relevant observations. Our study provides a simple but realistic mathematical ...
Source: Computational and Mathematical Methods in Medicine - January 13, 2021 Category: Statistics Tags: Comput Math Methods Med Source Type: research

Prediction of the Dental Arch Perimeter in a Kurdish Sample in Sulaimani City Based on Other Linear Dental Arch Measurements as a Malocclusion Preventive Measure.
Authors: Kareem FA, Rauf AM, Noori AJ, Ali Mahmood TM Abstract The current study aimed to find a prediction equation to estimate the arch perimeter (AP) depending on various arch dimensions including intercanine width (ICW), intermolar width (IMW), interpremolar width (IPMW), and arch length (AL) in a sample of the Kurdish population in Sulaimani City. The study sample was 100 pairs of preorthodontic dental casts. Calculations of dental arch dimensions and perimeter were performed by a digital vernier. Statistical analysis was performed via using the SPSS version 25 software. The developed prediction equation for t...
Source: Computational and Mathematical Methods in Medicine - January 13, 2021 Category: Statistics Tags: Comput Math Methods Med Source Type: research

How to Determine the Early Warning Threshold Value of Meteorological Factors on Influenza through Big Data Analysis and Machine Learning.
Authors: Ge H, Fan D, Wan M, Jin L, Wang X, Du X, Yang X Abstract Infectious diseases are a major health challenge for the worldwide population. Since their rapid spread can cause great distress to the real world, in addition to taking appropriate measures to curb the spread of infectious diseases in the event of an outbreak, proper prediction and early warning before the outbreak of the threat of infectious diseases can provide an important basis for early and reasonable response by the government health sector, reduce morbidity and mortality, and greatly reduce national losses. However, if only traditional medica...
Source: Computational and Mathematical Methods in Medicine - December 23, 2020 Category: Statistics Tags: Comput Math Methods Med Source Type: research

Assessment of Three Mathematical Prediction Models for Forecasting the COVID-19 Outbreak in Iran and Turkey.
In this study, three explicit mathematical prediction models were applied to forecast the COVID-19 outbreak in Iran and Turkey. These models include a recursive-based method, Boltzmann Function-based model and Beesham's prediction model. These models were exploited to analyze the confirmed and death cases of the first 106 and 87 days of the COVID-19 outbreak in Iran and Turkey, respectively. This application indicates that the three models fail to predict the first 10 to 20 days of data, depending on the prediction model. On the other hand, the results obtained for the rest of the data demonstrate that the three prediction...
Source: Computational and Mathematical Methods in Medicine - December 13, 2020 Category: Statistics Tags: Comput Math Methods Med Source Type: research

Broad Learning Enhanced 1H-MRS for Early Diagnosis of Neuropsychiatric Systemic Lupus Erythematosus.
Authors: Li Y, Ge Z, Zhang Z, Shen Z, Wang Y, Zhou T, Wu R Abstract In this paper, we explore the potential of using the multivoxel proton magnetic resonance spectroscopy (1H-MRS) to diagnose neuropsychiatric systemic lupus erythematosus (NPSLE) with the assistance of a support vector machine broad learning system (BL-SVM). We retrospectively analysed 23 confirmed patients and 16 healthy controls, who underwent a 3.0 T magnetic resonance imaging (MRI) sequence with multivoxel 1H-MRS in our hospitals. One hundred and seventeen metabolic features were extracted from the multivoxel 1H-MRS image. Thirty-three me...
Source: Computational and Mathematical Methods in Medicine - December 13, 2020 Category: Statistics Tags: Comput Math Methods Med Source Type: research

Challenges to the Application of Spatially Explicit Stochastic Simulation Models for Foot-and-Mouth Disease Control in Endemic Settings: A Systematic Review.
Authors: Zaheer MU, Salman MD, Steneroden KK, Magzamen SL, Weber SE, Case S, Rao S Abstract Simulation modeling has become common for estimating the spread of highly contagious animal diseases. Several models have been developed to mimic the spread of foot-and-mouth disease (FMD) in specific regions or countries, conduct risk assessment, analyze outbreaks using historical data or hypothetical scenarios, assist in policy decisions during epidemics, formulate preparedness plans, and evaluate economic impacts. Majority of the available FMD simulation models were designed for and applied in disease-free countries, whil...
Source: Computational and Mathematical Methods in Medicine - December 11, 2020 Category: Statistics Tags: Comput Math Methods Med Source Type: research

PredAmyl-MLP: Prediction of Amyloid Proteins Using Multilayer Perceptron.
Authors: Li Y, Zhang Z, Teng Z, Liu X Abstract Amyloid is generally an aggregate of insoluble fibrin; its abnormal deposition is the pathogenic mechanism of various diseases, such as Alzheimer's disease and type II diabetes. Therefore, accurately identifying amyloid is necessary to understand its role in pathology. We proposed a machine learning-based prediction model called PredAmyl-MLP, which consists of the following three steps: feature extraction, feature selection, and classification. In the step of feature extraction, seven feature extraction algorithms and different combinations of them are investigated, an...
Source: Computational and Mathematical Methods in Medicine - December 11, 2020 Category: Statistics Tags: Comput Math Methods Med Source Type: research

Modeling the Effects of Helminth Infection on the Transmission Dynamics of Mycobacterium tuberculosis under Optimal Control Strategies.
Authors: Lambura AG, Mwanga GG, Luboobi L, Kuznetsov D Abstract A deterministic mathematical model for the transmission and control of cointeraction of helminths and tuberculosis is presented, to examine the impact of helminth on tuberculosis and the effect of control strategies. The equilibrium point is established, and the effective reproduction number is computed. The disease-free equilibrium point is confirmed to be asymptotically stable whenever the effective reproduction number is less than the unit. The analysis of the effective reproduction number indicates that an increase in the helminth cases increases t...
Source: Computational and Mathematical Methods in Medicine - December 8, 2020 Category: Statistics Tags: Comput Math Methods Med Source Type: research

Condition for Global Stability for a SEIR Model Incorporating Exogenous Reinfection and Primary Infection Mechanisms.
Authors: Wangari IM Abstract A mathematical model incorporating exogenous reinfection and primary progression infection processes is proposed. Global stability is examined using the geometric approach which involves the generalization of Poincare-Bendixson criterion for systems of n-ordinary differential equations. Analytical results show that for a Susceptible-Exposed-Infective-Recovered (SEIR) model incorporating exogenous reinfection and primary progression infection mechanisms, an additional condition is required to fulfill the Bendixson criterion for global stability. That is, the model is globally asymptotica...
Source: Computational and Mathematical Methods in Medicine - December 8, 2020 Category: Statistics Tags: Comput Math Methods Med Source Type: research

Risk Factors of Cerebral Infarction and Myocardial Infarction after Carotid Endarterectomy Analyzed by Machine Learning.
Conclusion: Eight factors, such as blood pressure, body mass index, and age, may be related to the postoperative cerebral infarction and myocardial infarction in patients with CEA. The machine learning method deserves further study. PMID: 33273961 [PubMed - in process] (Source: Computational and Mathematical Methods in Medicine)
Source: Computational and Mathematical Methods in Medicine - December 5, 2020 Category: Statistics Tags: Comput Math Methods Med Source Type: research

Randomness for Nucleotide Sequences of SARS-CoV-2 and Its Related Subfamilies.
Authors: Chen RM Abstract The origin and evolution of SARS-CoV-2 has been an important issue in tackling COVID-19. Research on these topics would enhance our knowledge of this virus and help us develop vaccines or predict its paths of mutations. There are many theoretical and clinical researches in this area. In this article, we devise a structural metric which directly measures the structural differences between any two nucleotide sequences. In order to explore the mechanisms of how the evolution works, we associate the nucleotide sequences of SARS-CoV-2 and its related families with the degrees of randomness. Sin...
Source: Computational and Mathematical Methods in Medicine - December 5, 2020 Category: Statistics Tags: Comput Math Methods Med Source Type: research

Identification of Prognostic Biomarkers of Cutaneous Melanoma Based on Analysis of Tumor Mutation Burden.
Conclusion: Our study demonstrated that a higher TMB was associated with favorable survival outcome in cutaneous melanoma. Moreover, a close association between prognostic model and immune infiltration was identified, providing a new potential target for immunotherapy. PMID: 33273963 [PubMed - in process] (Source: Computational and Mathematical Methods in Medicine)
Source: Computational and Mathematical Methods in Medicine - December 5, 2020 Category: Statistics Tags: Comput Math Methods Med Source Type: research

SARPPIC: Exploiting COVID-19 Contact Tracing Recommendation through Social Awareness.
Authors: Asabere NY, Acakpovi A, Ofori EK, Torgby W, Kuuboore M, Lawson G, Adjaloko E Abstract Globally, the current coronavirus disease 2019 (COVID-19) pandemic is resulting in high fatality rates. Consequently, the prevention of further transmission is very vital. Until vaccines are widely available, the only available infection prevention methods include the following: contact tracing, case isolation and quarantine, social (physical) distancing, and hygiene measures (washing of hands with soap and water and using alcohol-based hand sanitizers). Contact tracing, which is key in preventing the spread of COVID-19, ...
Source: Computational and Mathematical Methods in Medicine - November 24, 2020 Category: Statistics Tags: Comput Math Methods Med Source Type: research

Succinylation Site Prediction Based on Protein Sequences Using the IFS-LightGBM (BO) Model.
In this study, we develop a new model, IFS-LightGBM (BO), which utilizes the incremental feature selection (IFS) method, the LightGBM feature selection method, the Bayesian optimization algorithm, and the LightGBM classifier, to predict succinylation sites in proteins. Specifically, pseudo amino acid composition (PseAAC), position-specific scoring matrix (PSSM), disorder status, and Composition of k-spaced Amino Acid Pairs (CKSAAP) are firstly employed to extract feature information. Then, utilizing the combination of the LightGBM feature selection method and the incremental feature selection (IFS) method selects the optim...
Source: Computational and Mathematical Methods in Medicine - November 24, 2020 Category: Statistics Tags: Comput Math Methods Med Source Type: research

The Use of System Dynamics Methodology in Building a COVID-19 Confirmed Case Model.
Authors: Mohd Yusoff MI Abstract Researchers used a hybrid model (a combination of health resource demand model and disease transmission model), Bayesian model, and susceptible-exposed-infectious-removed (SEIR) model to predict health service utilization and deaths and mixed-effect nonlinear regression. Further, they used the mixture model to predict the number of confirmed cases and deaths or to predict when the curve would flatten. In this article, we show, through scenarios developed using system dynamics methodology, besides close to real-world results, the detrimental effects of ignoring social distancing guid...
Source: Computational and Mathematical Methods in Medicine - November 24, 2020 Category: Statistics Tags: Comput Math Methods Med Source Type: research

Comprehensive Analysis of Differently Expressed and Methylated Genes in Preeclampsia.
Authors: Xu W, Ru P, Gu Z, Zhang R, Pang X, Huang Y, Liu Z, Liu M Abstract Preeclampsia (PE) is one of the mainly caused maternal and infant incidences and mortalities worldwide. However, the mechanisms underlying PE remained largely unclear. The present study identified 1716 high expressions of gene and 2705 low expressions of gene using GSE60438 database, and identified 7087 hypermethylated and 15120 hypomethylated genes in preeclampsia using GSE100197. Finally, 536 upregulated genes with hypomethylation and 322 downregulated genes with hypermethylation were for the first time revealed in PE. Gene Ontology (GO) a...
Source: Computational and Mathematical Methods in Medicine - November 21, 2020 Category: Statistics Tags: Comput Math Methods Med Source Type: research

miR-139-5p Inhibits Lung Adenocarcinoma Cell Proliferation, Migration, and Invasion by Targeting MAD2L1.
Conclusion: Our study suggests that miR-139-5p is lowly expressed in LUAD cells and inhibits LUAD cell proliferation, migration, and invasion by targeted suppressing MAD2L1 expression. It is of potential significance for the prognosis and treatment of LUAD. PMID: 33204298 [PubMed - in process] (Source: Computational and Mathematical Methods in Medicine)
Source: Computational and Mathematical Methods in Medicine - November 21, 2020 Category: Statistics Tags: Comput Math Methods Med Source Type: research

DRG-Oriented Mathematical Calculation Model and Method of Integrated Medical Service Cost.
In this study, activity-based costing and weighted moving average methods are used. First, basic data of medical services are collected, then all medical activities are confirmed and all service costs are collected, then a cost database is established, and a calculation model of medical costs is designed. Finally, calculation suggestions and optimization methods are put forward by analyzing the calculated data. The experimental results show that the actual demand of drugs predicted by the general moving average method is relatively insufficient, with the maximum error of 41%, the minimum of 5%, and the average error of 19....
Source: Computational and Mathematical Methods in Medicine - November 21, 2020 Category: Statistics Tags: Comput Math Methods Med Source Type: research

Segmentation of Intensity-Corrupted Medical Images Using Adaptive Weight-Based Hybrid Active Contours.
Authors: Memon AA, Soomro S, Shahid MT, Munir A, Niaz A, Choi KN Abstract Segmentation accuracy is an important criterion for evaluating the performance of segmentation techniques used to extract objects of interest from images, such as the active contour model. However, segmentation accuracy can be affected by image artifacts such as intensity inhomogeneity, which makes it difficult to extract objects with inhomogeneous intensities. To address this issue, this paper proposes a hybrid region-based active contour model for the segmentation of inhomogeneous images. The proposed hybrid energy functional combines local...
Source: Computational and Mathematical Methods in Medicine - November 21, 2020 Category: Statistics Tags: Comput Math Methods Med Source Type: research

A Multifeature Extraction Method Using Deep Residual Network for MR Image Denoising.
Authors: Yao L Abstract In order to improve the resolution of magnetic resonance (MR) image and reduce the interference of noise, a multifeature extraction denoising algorithm based on a deep residual network is proposed. First, the feature extraction layer is constructed by combining three different sizes of convolution kernels, which are used to obtain multiple shallow features for fusion and increase the network's multiscale perception ability. Then, it combines batch normalization and residual learning technology to accelerate and optimize the deep network, while solving the problem of internal covariate transf...
Source: Computational and Mathematical Methods in Medicine - November 21, 2020 Category: Statistics Tags: Comput Math Methods Med Source Type: research

An Integrating Immune-Related Signature to Improve Prognosis of Hepatocellular Carcinoma.
Authors: Zhu R, Guo W, Xu XJ, Zhu L Abstract Growing evidence suggests that the superiority of long noncoding RNAs (lncRNAs) and messenger RNAs (mRNAs) could act as biomarkers for cancer prognosis. However, the prognostic marker for hepatocellular carcinoma with high accuracy and sensitivity is still lacking. In this research, a retrospective, cohort-based study of genome-wide RNA-seq data of patients with hepatocellular carcinoma was carried out, and two protein-coding genes (GTPBP4, TREM-1) and one lncRNA (LINC00426) were sorted out to construct an integrative signature to predict the prognosis of patients. The r...
Source: Computational and Mathematical Methods in Medicine - November 21, 2020 Category: Statistics Tags: Comput Math Methods Med Source Type: research

Using Convolutional Neural Network with Cheat Sheet and Data Augmentation to Detect Breast Cancer in Mammograms.
In this study, a novel procedure to aid imaging specialists in detecting normal and abnormal mammograms has been proposed. The procedure supplied the designed CNN with a cheat sheet for some classical attributes extracted from the ROI and an extra number of labeled mammograms through data augmentation. The cheat sheet aided the CNN through encoding easy-to-recognize artificial patterns in the mammogram before passing it to the CNN, and the data augmentation supported the CNN with more labeled data points. Fifteen runs of 4 different modified datasets taken from the MIAS dataset were conducted and analyzed. The results show...
Source: Computational and Mathematical Methods in Medicine - November 18, 2020 Category: Statistics Tags: Comput Math Methods Med Source Type: research

Polygonally Meshed Dipole Model Simulation of the Electrical Field Produced by the Stomach and Intestines.
In this study, we propose a novel polygonally meshed dipole model to conveniently reproduce ECA based on the movement of the annular band in complex shapes, such as the shape of the stomach and intestines, constructed in three-dimensional (3D) space. We show that the proposed model can reproduce ECA simulation results similar to those obtained using conventional models. Moreover, we show that the proposed model can reproduce the ECA produced by a complex geometrical shape, such as the shape of the intestines. The study results indicate that ECA simulations can be conducted based on structures that more closely resemble rea...
Source: Computational and Mathematical Methods in Medicine - November 14, 2020 Category: Statistics Tags: Comput Math Methods Med Source Type: research

Modelling the Potential Impact of Social Distancing on the COVID-19 Epidemic in South Africa.
Authors: Nyabadza F, Chirove F, Chukwu CW, Visaya MV Abstract The novel coronavirus (COVID-19) pandemic continues to be a global health problem whose impact has been significantly felt in South Africa. With the global spread increasing and infecting millions, containment efforts by countries have largely focused on lockdowns and social distancing to minimise contact between persons. Social distancing has been touted as the best form of response in managing a rapid increase in the number of infected cases. In this paper, we present a deterministic model to describe the impact of social distancing on the transmission...
Source: Computational and Mathematical Methods in Medicine - November 14, 2020 Category: Statistics Tags: Comput Math Methods Med Source Type: research

A Simple Framework of Smart Geriatric Nursing considering Health Big Data and User Profile.
Authors: Li S, Tang Y Abstract The National Bureau of Statistics of China shows that the population over 65 years old in China exceeds 166 million accounting for 11.93% of the total population by the end of 2018. The importance and severity of taking care of the elderly are becoming increasingly prominent. High-quality and meticulous care for the daily life of the elderly needs helpful and advanced sciences and technologies. Smart geriatric nursing is a must. Basing on the professional knowledge of geriatric nursing, this paper proposes a framework of smart geriatric nursing which consists of three aspects of smart...
Source: Computational and Mathematical Methods in Medicine - November 7, 2020 Category: Statistics Tags: Comput Math Methods Med Source Type: research

Gene Expression Profiling of Type 2 Diabetes Mellitus by Bioinformatics Analysis.
Conclusion: Our data provide a comprehensive bioinformatics analysis of genes, functions, and pathways, which may be related to the pathogenesis of T2DM. PMID: 33149760 [PubMed - in process] (Source: Computational and Mathematical Methods in Medicine)
Source: Computational and Mathematical Methods in Medicine - November 7, 2020 Category: Statistics Tags: Comput Math Methods Med Source Type: research

Evaluation of Multimodal Algorithms for the Segmentation of Multiparametric MRI Prostate Images.
Authors: Nai YH, Teo BW, Tan NL, Chua KYW, Wong CK, O'Doherty S, Stephenson MC, Schaefferkoetter J, Thian YL, Chiong E, Reilhac A Abstract Prostate segmentation in multiparametric magnetic resonance imaging (mpMRI) can help to support prostate cancer diagnosis and therapy treatment. However, manual segmentation of the prostate is subjective and time-consuming. Many deep learning monomodal networks have been developed for automatic whole prostate segmentation from T2-weighted MR images. We aimed to investigate the added value of multimodal networks in segmenting the prostate into the peripheral zone (PZ) and central...
Source: Computational and Mathematical Methods in Medicine - November 5, 2020 Category: Statistics Tags: Comput Math Methods Med Source Type: research

circFAT1(e2) Promotes Papillary Thyroid Cancer Proliferation, Migration, and Invasion via the miRNA-873/ZEB1 Axis.
In conclusion, the results of this study indicated that circFAT1(e2) played a carcinogenic role by targeting the miR-873/ZEB1 axis to promote PTC invasion and metastasis, which might become a potential novel target for therapy of PTC. PMID: 33133224 [PubMed - in process] (Source: Computational and Mathematical Methods in Medicine)
Source: Computational and Mathematical Methods in Medicine - November 4, 2020 Category: Statistics Tags: Comput Math Methods Med Source Type: research

Wavelet Scattering Transform for ECG Beat Classification.
In this study, the wavelet scattering transform extracted 8 time windows from each ECG heartbeat. Two dimensionality reduction methods, principal component analysis (PCA) and time window selection, were applied on the 8 time windows. These processed features were fed to the neural network (NN), probabilistic neural network (PNN), and k-nearest neighbour (KNN) classifiers for classification. The 4th time window in combination with KNN (k = 4) has achieved the optimal performance with an averaged accuracy, positive predictive value, sensitivity, and specificity of 99.3%, 99.6%, 99.5%, and 98.8%, respectively, using tenfold c...
Source: Computational and Mathematical Methods in Medicine - November 4, 2020 Category: Statistics Tags: Comput Math Methods Med Source Type: research