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https://www.readbyqxmd.com/read/29332804/effect-of-preprocessing-high-resolution-mass-spectra-on-the-pattern-recognition-of-cannabis-hemp-and-liquor
#1
Xinyi Wang, Peter de B Harrington, Steven F Baugh
High-resolution mass spectrometry (HRMS) combined with pattern recognition was used to discriminate among twenty-five Cannabis samples, twenty hemp samples, and eight liquor samples. The effects of preprocessing on multivariate data analysis were evaluated for Orbitrap high-resolution mass spectra. Different root transformations were evaluated with respect to the bin width and the average classification rates. In addition, linear binning and proportional binning with various resolving powers were studied with respect to the average classification rates...
April 1, 2018: Talanta
https://www.readbyqxmd.com/read/29329226/plils-a-practical-indoor-localization-system-through-less-expensive-wireless-chips-via-subregion-clustering
#2
Xiaolong Li, Yifu Yang, Jun Cai, Yun Deng, Junfeng Yang, Xinmin Zhou, Lina Tan
Reducing costs is a pragmatic method for promoting the widespread usage of indoor localization technology. Conventional indoor localization systems (ILSs) exploit relatively expensive wireless chips to measure received signal strength for positioning. Our work is based on a cheap and widely-used commercial off-the-shelf (COTS) wireless chip, i.e., the Nordic Semiconductor nRF24LE1, which has only several output power levels, and proposes a new power level based-ILS, called Plils. The localization procedure incorporates two phases: an offline training phase and an online localization phase...
January 12, 2018: Sensors
https://www.readbyqxmd.com/read/29328377/feature-genes-in-metastatic-breast-cancer-identified-by-metade-and-svm-classifier-methods
#3
Youlin Tuo, Ning An, Ming Zhang
The aim of the present study was to investigate the feature genes in metastatic breast cancer samples. A total of 5 expression profiles of metastatic breast cancer samples were downloaded from the Gene Expression Omnibus database, which were then analyzed using the MetaQC and MetaDE packages in R language. The feature genes between metastasis and non‑metastasis samples were screened under the threshold of P<0.05. Based on the protein‑protein interactions (PPIs) in the Biological General Repository for Interaction Datasets, Human Protein Reference Database and Biomolecular Interaction Network Database, the PPI network of the feature genes was constructed...
January 9, 2018: Molecular Medicine Reports
https://www.readbyqxmd.com/read/29328363/support-vector-machine-classifier-for-prediction-of-the-metastasis-of-colorectal-cancer
#4
Jiajun Zhi, Jiwei Sun, Zhongchuan Wang, Wenjun Ding
Colorectal cancer (CRC) is one of the most common cancers and a major cause of mortality. The present study aimed to identify potential biomarkers for CRC metastasis and uncover the mechanisms underlying the etiology of the disease. The five datasets GSE68468, GSE62321, GSE22834, GSE14297 and GSE6988 were utilized in the study, all of which contained metastatic and non-metastatic CRC samples. Among them, three datasets were integrated via meta-analysis to identify the differentially expressed genes (DEGs) between the two types of samples...
January 2, 2018: International Journal of Molecular Medicine
https://www.readbyqxmd.com/read/29326805/detection-of-%C3%AE-thalassemia-carriers-by-red-cell-parameters-obtained-from-automatic-counters-using-mathematical-formulas
#5
Idit Lachover Roth, Boaz Lachover, Guy Koren, Carina Levin, Luci Zalman, Ariel Koren
Background: β-thalassemia major is a severe disease with high morbidity. The world prevalence of carriers is around 1.5-7%. The present study aimed to find a reliable formula for detecting β-thalassemia carriers using an extensive database of more than 22,000 samples obtained from a homogeneous population of childbearing age women with 3161 (13.6%) of β-thalassemia carriers and to check previously published formulas. Methods: We applied a mathematical method based on the support vector machine (SVM) algorithm in the search for a reliable formula that can differentiate between thalassemia carriers and non-carriers, including normal counts or counts suspected to belong to iron-deficient women...
2018: Mediterranean Journal of Hematology and Infectious Diseases
https://www.readbyqxmd.com/read/29325342/-computer-aided-diagnosis-system-of-breast-ultrasound-based-on-support-vector-machine-a-clinical-analysis
#6
Z W Chen, H M Wang, J B Wu, X Y Wang, M Lin, Y Lin, H H Zhang, B J Ten, X X Huang
Objective: To investigate the value of based on support vector machine (SVM) breast ultrasonography technology of Computer-Assisted diagnosis (CAD) for differential diagnosis of benign and malignant breast masses. Methods: Total of 143 patients who had 151 breast masses were collected in Fujian Maternity and Children Health Hospital or The Fist Affiliated Hospital of Fujian Medical University from June 2014 to December 2015. Based on pathological results as the gold standard, the diagnostic efficiency of CAD and ultrasonography were compared...
December 26, 2017: Zhonghua Yi Xue za Zhi [Chinese medical journal]
https://www.readbyqxmd.com/read/29323408/prediction-analysis-and-quality-assessment-of-microwell-array-images
#7
Hirak Mazumdar, Tae Hyeon Kim, Jong Min Lee, Jang Ho Ha, Christian D Ahrberg, Bong Geun Chung
Microwell arrays are widely used sensor for the analysis of fluorescent-labelled biomaterials. For rapid detection and automated analysis of microwell arrays, the computational image analysis is required. Support Vector Machines (SVM) can be used for this task. Here, we present a SVM-based approach for the analysis of microwell arrays consisting of three distinct steps: labeling, training for feature selection, and classification into three classes. The three classes are filled, partially filled, and unfilled microwells...
January 11, 2018: Electrophoresis
https://www.readbyqxmd.com/read/29322938/mdd-carb-a-combinatorial-model-for-the-identification-of-protein-carbonylation-sites-with-substrate-motifs
#8
Hui-Ju Kao, Shun-Long Weng, Kai-Yao Huang, Fergie Joanda Kaunang, Justin Bo-Kai Hsu, Chien-Hsun Huang, Tzong-Yi Lee
BACKGROUND: Carbonylation, which takes place through oxidation of reactive oxygen species (ROS) on specific residues, is an irreversibly oxidative modification of proteins. It has been reported that the carbonylation is related to a number of metabolic or aging diseases including diabetes, chronic lung disease, Parkinson's disease, and Alzheimer's disease. Due to the lack of computational methods dedicated to exploring motif signatures of protein carbonylation sites, we were motivated to exploit an iterative statistical method to characterize and identify carbonylated sites with motif signatures...
December 21, 2017: BMC Systems Biology
https://www.readbyqxmd.com/read/29322919/hadamard-kernel-svm-with-applications-for-breast-cancer-outcome-predictions
#9
Hao Jiang, Wai-Ki Ching, Wai-Shun Cheung, Wenpin Hou, Hong Yin
BACKGROUND: Breast cancer is one of the leading causes of deaths for women. It is of great necessity to develop effective methods for breast cancer detection and diagnosis. Recent studies have focused on gene-based signatures for outcome predictions. Kernel SVM for its discriminative power in dealing with small sample pattern recognition problems has attracted a lot attention. But how to select or construct an appropriate kernel for a specified problem still needs further investigation...
December 21, 2017: BMC Systems Biology
https://www.readbyqxmd.com/read/29322221/feasibility-of-opportunistic-osteoporosis-screening-in-routine-contrast-enhanced-multi-detector-computed-tomography-mdct-using-texture-analysis
#10
M R K Mookiah, A Rohrmeier, M Dieckmeyer, K Mei, F K Kopp, P B Noel, J S Kirschke, T Baum, K Subburaj
This study investigated the feasibility of opportunistic osteoporosis screening in routine contrast-enhanced MDCT exams using texture analysis. The results showed an acceptable reproducibility of texture features, and these features could discriminate healthy/osteoporotic fracture cohort with an accuracy of 83%. INTRODUCTION: This aim of this study is to investigate the feasibility of opportunistic osteoporosis screening in routine contrast-enhanced MDCT exams using texture analysis. METHODS: We performed texture analysis at the spine in routine MDCT exams and investigated the effect of intravenous contrast medium (IVCM) (n = 7), slice thickness (n = 7), the long-term reproducibility (n = 9), and the ability to differentiate healthy/osteoporotic fracture cohort (n = 9 age and gender matched pairs)...
January 10, 2018: Osteoporosis International
https://www.readbyqxmd.com/read/29321645/mri-features-predictive-of-negative-surgical-margins-in-patients-with-her2-overexpressing-breast-cancer-undergoing-breast-conservation
#11
Brittany Z Dashevsky, Jung Hun Oh, Aditya P Apte, Blanca Bernard-Davila, Elizabeth A Morris, Joseph O Deasy, Elizabeth J Sutton
Here we develop a tool to predict resectability of HER2+ breast cancer at breast conservation surgery (BCS) utilizing features identified on preoperative breast MRI. We identified patients with HER2+ breast cancer who obtained pre-operative breast MRI and underwent BCS between 2002-2013. From the contoured tumor on pre-operative MRI, shape, histogram, and co-occurrence and size zone matrix texture features were extracted. In univariate analysis, Spearman's correlation coefficient (Rs) was used to assess the correlation between each image feature and an endpoint (surgical re-excision)...
January 10, 2018: Scientific Reports
https://www.readbyqxmd.com/read/29320986/revealing-alzheimer-s-disease-genes-spectrum-in-the-whole-genome-by-machine-learning
#12
Xiaoyan Huang, Hankui Liu, Xinming Li, Liping Guan, Jiankang Li, Laurent Christian Asker M Tellier, Huanming Yang, Jian Wang, Jianguo Zhang
BACKGROUND: Alzheimer's disease (AD) is an important, progressive neurodegenerative disease, with a complex genetic architecture. A key goal of biomedical research is to seek out disease risk genes, and to elucidate the function of these risk genes in the development of disease. For this purpose, expanding the AD-associated gene set is necessary. In past research, the prediction methods for AD related genes has been limited in their exploration of the target genome regions. We here present a genome-wide method for AD candidate genes predictions...
January 10, 2018: BMC Neurology
https://www.readbyqxmd.com/read/29320579/emotional-modelling-and-classification-of-a-large-scale-collection-of-scene-images-in-a-cluster-environment
#13
Jianfang Cao, Yanfei Li, Yun Tian
The development of network technology and the popularization of image capturing devices have led to a rapid increase in the number of digital images available, and it is becoming increasingly difficult to identify a desired image from among the massive number of possible images. Images usually contain rich semantic information, and people usually understand images at a high semantic level. Therefore, achieving the ability to use advanced technology to identify the emotional semantics contained in images to enable emotional semantic image classification remains an urgent issue in various industries...
2018: PloS One
https://www.readbyqxmd.com/read/29318713/hybrid-feature-extraction-techniques-for-microscopic-hepatic-fibrosis-classification
#14
Dalia S Ashour, Dina M Abou Rayia, Mohamed Maher Ata, Amira S Ashour, Mustafa M Abd Elnaby
Chronic liver diseases' hallmark is the fibrosis that results in liver function failure in advanced stages. One of the serious parasitic diseases affecting the liver tissues is schistosomiasis. Immunologic reactions to Schistosoma eggs leads to accumulation of collagen in the hepatic parenchyma causing fibrosis. Thus, monitoring and reporting the staging of the histopathological information related to liver fibrosis are essential for accurate diagnosis and therapy of the chronic liver diseases. Automated assessment of the microscopic liver tissue images is an essential process...
January 10, 2018: Microscopy Research and Technique
https://www.readbyqxmd.com/read/29316723/gas-classification-using-deep-convolutional-neural-networks
#15
Pai Peng, Xiaojin Zhao, Xiaofang Pan, Wenbin Ye
In this work, we propose a novel Deep Convolutional Neural Network (DCNN) tailored for gas classification. Inspired by the great success of DCNN in the field of computer vision, we designed a DCNN with up to 38 layers. In general, the proposed gas neural network, named GasNet, consists of: six convolutional blocks, each block consist of six layers; a pooling layer; and a fully-connected layer. Together, these various layers make up a powerful deep model for gas classification. Experimental results show that the proposed DCNN method is an effective technique for classifying electronic nose data...
January 8, 2018: Sensors
https://www.readbyqxmd.com/read/29316706/assessing-the-performances-of-protein-function-prediction-algorithms-from-the-perspectives-of-identification-accuracy-and-false-discovery-rate
#16
Chun Yan Yu, Xiao Xu Li, Hong Yang, Ying Hong Li, Wei Wei Xue, Yu Zong Chen, Lin Tao, Feng Zhu
The function of a protein is of great interest in the cutting-edge research of biological mechanisms, disease development and drug/target discovery. Besides experimental explorations, a variety of computational methods have been designed to predict protein function. Among these in silico methods, the prediction of BLAST is based on protein sequence similarity, while that of machine learning is also based on the sequence, but without the consideration of their similarity. This unique characteristic of machine learning makes it a good complement to BLAST and many other approaches in predicting the function of remotely relevant proteins and the homologous proteins of distinct function...
January 8, 2018: International Journal of Molecular Sciences
https://www.readbyqxmd.com/read/29315232/recognition-of-activities-of-daily-living-based-on-environmental-analyses-using-audio-fingerprinting-techniques-a-systematic-review
#17
REVIEW
Ivan Miguel Pires, Rui Santos, Nuno Pombo, Nuno M Garcia, Francisco Flórez-Revuelta, Susanna Spinsante, Rossitza Goleva, Eftim Zdravevski
An increase in the accuracy of identification of Activities of Daily Living (ADL) is very important for different goals of Enhanced Living Environments and for Ambient Assisted Living (AAL) tasks. This increase may be achieved through identification of the surrounding environment. Although this is usually used to identify the location, ADL recognition can be improved with the identification of the sound in that particular environment. This paper reviews audio fingerprinting techniques that can be used with the acoustic data acquired from mobile devices...
January 9, 2018: Sensors
https://www.readbyqxmd.com/read/29314757/machine-learning-for-identifying-randomized-controlled-trials-an-evaluation-and-practitioner-s-guide
#18
Iain Marshall, Anna Noel Storr, Joël Kuiper, James Thomas, Byron C Wallace
Machine learning (ML) algorithms have proven highly accurate for identifying Randomized Controlled Trials (RCTs), but are not used much in practice, in part because the best way to make use of the technology in a typical workflow is unclear. In this work we evaluate ML models for RCT classification (Support Vector Machines [SVMs], Convolutional Neural Networks [CNNs], and ensemble approaches). We trained and optimised SVM and CNN models on the titles and abstracts of the Cochrane Crowd RCT set. We evaluated the models on an external dataset (Clinical Hedges), allowing direct comparison with traditional database search filters...
January 4, 2018: Research Synthesis Methods
https://www.readbyqxmd.com/read/29314345/differentiation-between-vasogenic-edema-and-infiltrative-tumor-in-patients-with-high-grade-gliomas-using-texture-patch-based-analysis
#19
Moran Artzi, Gilad Liberman, Deborah T Blumenthal, Orna Aizenstein, Felix Bokstein, Dafna Ben Bashat
BACKGROUND: High-grade gliomas (HGGs) induce both vasogenic edema and extensive infiltration of tumor cells, both of which present with similar appearance on conventional MRI. Using current radiological criteria, differentiation between these tumoral and nontumoral areas within the nonenhancing lesion area remains challenging. PURPOSE: To use radiomics patch-based analysis, based on conventional MRI, for the classification of the nonenhancing lesion area in patients with HGG into tumoral and nontumoral components...
January 3, 2018: Journal of Magnetic Resonance Imaging: JMRI
https://www.readbyqxmd.com/read/29306885/derivation-and-validation-of-different-machine-learning-models-in-mortality-prediction-of-trauma-in-motorcycle-riders-a-cross-sectional-retrospective-study-in-southern-taiwan
#20
Pao-Jen Kuo, Shao-Chun Wu, Peng-Chen Chien, Cheng-Shyuan Rau, Yi-Chun Chen, Hsiao-Yun Hsieh, Ching-Hua Hsieh
OBJECTIVES: This study aimed to build and test the models of machine learning (ML) to predict the mortality of hospitalised motorcycle riders. SETTING: The study was conducted in a level-1 trauma centre in southern Taiwan. PARTICIPANTS: Motorcycle riders who were hospitalised between January 2009 and December 2015 were classified into a training set (n=6306) and test set (n=946). Using the demographic information, injury characteristics and laboratory data of patients, logistic regression (LR), support vector machine (SVM) and decision tree (DT) analyses were performed to determine the mortality of individual motorcycle riders, under different conditions, using all samples or reduced samples, as well as all variables or selected features in the algorithm...
January 5, 2018: BMJ Open
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