keyword
MENU ▼
Read by QxMD icon Read
search

Support vector machine

keyword
https://www.readbyqxmd.com/read/28086902/exploiting-temporal-and-nonstationary-features-in-breathing-sound-analysis-for-multiple-obstructive-sleep-apnea-severity-classification
#1
Jaepil Kim, Taehoon Kim, Donmoon Lee, Jeong-Whun Kim, Kyogu Lee
BACKGROUND: Polysomnography (PSG) is the gold standard test for obstructive sleep apnea (OSA), but it incurs high costs, requires inconvenient measurements, and is limited by a one-night test. Thus, a repetitive OSA screening test using affordable data would be effective both for patients interested in their own OSA risk and in-hospital PSG. The purpose of this research was to develop a four-OSA severity classification model using a patient's breathing sounds. METHODS: Breathing sounds were recorded from 83 subjects during a PSG test...
January 7, 2017: Biomedical Engineering Online
https://www.readbyqxmd.com/read/28086747/microrna-based-pan-cancer-diagnosis-and-treatment-recommendation
#2
Nikhil Cheerla, Olivier Gevaert
BACKGROUND: The current state-of-the-art in cancer diagnosis and treatment is not ideal; diagnostic tests are accurate but invasive, and treatments are "one-size fits-all" instead of being personalized. Recently, miRNA's have garnered significant attention as cancer biomarkers, owing to their ease of access (circulating miRNA in the blood) and stability. There have been many studies showing the effectiveness of miRNA data in diagnosing specific cancer types, but few studies explore the role of miRNA in predicting treatment outcome...
January 13, 2017: BMC Bioinformatics
https://www.readbyqxmd.com/read/28079126/detecting-n-6-methyladenosine-sites-from-rna-transcriptomes-using-ensemble-support-vector-machines
#3
Wei Chen, Pengwei Xing, Quan Zou
As one of the most abundant RNA post-transcriptional modifications, N(6)-methyladenosine (m(6)A) involves in a broad spectrum of biological and physiological processes ranging from mRNA splicing and stability to cell differentiation and reprogramming. However, experimental identification of m(6)A sites is expensive and laborious. Therefore, it is urgent to develop computational methods for reliable prediction of m(6)A sites from primary RNA sequences. In the current study, a new method called RAM-ESVM was developed for detecting m(6)A sites from Saccharomyces cerevisiae transcriptome, which employed ensemble support vector machine classifiers and novel sequence features...
January 12, 2017: Scientific Reports
https://www.readbyqxmd.com/read/28079016/fast-hplc-fingerprinting-to-discriminate-olive-oil-from-other-edible-vegetable-oils-by-multivariate-classification-methods
#4
Ana M Jiménez-Carvelo, Antonio González-Casado, Estefanía Pérez-Castaño, Luis Cuadros-Rodríguez
A new analytical method for the differentiation of olive oil from other vegetable oils using reversed-phase LC and applying chemometric techniques was developed. A 3 cm short column was used to obtain the chromatographic fingerprint of the methyl-transesterified fraction of each vegetable oil. The chromatographic analysis took only 4 min. The multivariate classification methods used were <em>k</em>-nearest neighbors, partial least-squares (PLS) discriminant analysis, one-class PLS, support vector machine classification, and soft independent modeling of class analogies...
January 12, 2017: Journal of AOAC International
https://www.readbyqxmd.com/read/28075375/an-approach-to-biometric-verification-based-on-human-body-communication-in-wearable-devices
#5
Jingzhen Li, Yuhang Liu, Zedong Nie, Wenjian Qin, Zengyao Pang, Lei Wang
In this paper, an approach to biometric verification based on human body communication (HBC) is presented for wearable devices. For this purpose, the transmission gain S21 of volunteer's forearm is measured by vector network analyzer (VNA). Specifically, in order to determine the chosen frequency for biometric verification, 1800 groups of data are acquired from 10 volunteers in the frequency range 0.3 MHz to 1500 MHz, and each group includes 1601 sample data. In addition, to achieve the rapid verification, 30 groups of data for each volunteer are acquired at the chosen frequency, and each group contains only 21 sample data...
January 10, 2017: Sensors
https://www.readbyqxmd.com/read/28074598/prediction-of-skin-sensitization-potency-using-machine-learning-approaches
#6
Qingda Zang, Michael Paris, David M Lehmann, Shannon Bell, Nicole Kleinstreuer, David Allen, Joanna Matheson, Abigail Jacobs, Warren Casey, Judy Strickland
The replacement of animal use in testing for regulatory classification of skin sensitizers is a priority for US federal agencies that use data from such testing. Machine learning models that classify substances as sensitizers or non-sensitizers without using animal data have been developed and evaluated. Because some regulatory agencies require that sensitizers be further classified into potency categories, we developed statistical models to predict skin sensitization potency for murine local lymph node assay (LLNA) and human outcomes...
January 10, 2017: Journal of Applied Toxicology: JAT
https://www.readbyqxmd.com/read/28073756/feature-selection-using-a-one-dimensional-na%C3%A3-ve-bayes-classifier-increases-the-accuracy-of-support-vector-machine-classification-of-cdr3-repertoires
#7
Mattia Cinelli, Yuxin Sun, Katharine Best, James M Heather, Shlomit Reich-Zeliger, Eric Shifrut, Nir Friedman, John Shawe-Taylor, Benny Chain
MOTIVATION: Somatic DNA recombination, the hallmark of vertebrate adaptive immunity, has the potential to generate a vast diversity of antigen receptor sequences. How this diversity captures antigen specificity remains incompletely understood. In this study we use high throughput sequencing to compare the global changes in T cell receptor β chain complementarity determining region 3 (CDR3β) sequences following immunization with ovalbumin administered with complete Freund's adjuvant (CFA) or CFA alone...
January 10, 2017: Bioinformatics
https://www.readbyqxmd.com/read/28072829/predicting-the-metabolic-sites-by-flavin-containing-monooxygenase-on-drug-molecules-using-svm-classification-on-computed-quantum-mechanics-and-circular-fingerprints-molecular-descriptors
#8
Chien-Wei Fu, Thy-Hou Lin
As an important enzyme in Phase I drug metabolism, the flavin-containing monooxygenase (FMO) also metabolizes some xenobiotics with soft nucleophiles. The site of metabolism (SOM) on a molecule is the site where the metabolic reaction is exerted by an enzyme. Accurate prediction of SOMs on drug molecules will assist the search for drug leads during the optimization process. Here, some quantum mechanics features such as the condensed Fukui function and attributes from circular fingerprints (called Molprint2D) are computed and classified using the support vector machine (SVM) for predicting some potential SOMs on a series of drugs that can be metabolized by FMO enzymes...
2017: PloS One
https://www.readbyqxmd.com/read/28071843/automated-measurement-of-pressure-injury-through-image-processing
#9
Dan Li, Carol Mathews
AIMS AND OBJECTIVES: Develop an image processing algorithm to automatically measure pressure injuries using electronic pressure injury images stored in nursing documentation. BACKGROUND: Photographing pressure injuries and storing the images in the electronic health record is standard practice in many hospitals. However, the manual measurement of pressure injury is time-consuming, challenging, and subject to intra-inter-reader variability with complexities of the pressure injury and the clinical environment...
January 10, 2017: Journal of Clinical Nursing
https://www.readbyqxmd.com/read/28070749/an-automated-microemboli-detection-and-classification-system-using-backscatter-rf-signals-and-differential-evolution
#10
Karim Ferroudji, Nabil Benoudjit, Ayache Bouakaz
Embolic phenomena, whether air or particulate emboli, can induce immediate damages like heart attack or ischemic stroke. Embolus composition (gaseous or particulate matter) is vital in predicting clinically significant complications. Embolus detection using Doppler methods have shown their limits to differentiate solid and gaseous embolus. Radio-frequency (RF) ultrasound signals backscattered by the emboli contain additional information on the embolus in comparison to the traditionally used Doppler signals...
January 9, 2017: Australasian Physical & Engineering Sciences in Medicine
https://www.readbyqxmd.com/read/28068348/optical-determination-of-lead-chrome-green-in-green-tea-by-fourier-transform-infrared-ft-ir-transmission-spectroscopy
#11
Xiaoli Li, Kaiwen Xu, Yuying Zhang, Chanjun Sun, Yong He
The potential of Fourier transform infrared (FT-IR) transmission spectroscopy for determination of lead chrome green in green tea was investigated based on chemometric methods. Firstly, the qualitative analysis of lead chrome green in tea was performed based on partial least squares discriminant analysis (PLS-DA), and the correct rate of classification was 100%. And then, a hybrid method of interval partial least squares (iPLS) regression and successive projections algorithm (SPA) was proposed to select characteristic wavenumbers for the quantitative analysis of lead chrome green in green tea, and 19 wavenumbers were obtained finally...
2017: PloS One
https://www.readbyqxmd.com/read/28068295/support-vector-machines-to-detect-physiological-patterns-for-eeg-and-emg-based-human-computer-interaction-a-review
#12
L R Quitadamo, F Cavrini, L Sbernini, F Riillo, L Bianchi, S Seri, G Saggio
Support vector machines (SVMs) are widely used classifiers for detecting physiological patterns in human-computer interaction (HCI). Their success is due to their versatility, robustness and large availability of free dedicated toolboxes. Frequently in the literature, insufficient details about the SVM implementation and/or parameters selection are reported, making it impossible to reproduce study analysis and results. In order to perform an optimized classification and report a proper description of the results, it is necessary to have a comprehensive critical overview of the applications of SVM...
January 9, 2017: Journal of Neural Engineering
https://www.readbyqxmd.com/read/28068175/cpg-methylation-signature-predicts-recurrence-in-early-stage-hepatocellular-carcinoma-results-from-a-multicenter-study
#13
Jiliang Qiu, Baogang Peng, Yunqiang Tang, Yeben Qian, Pi Guo, Mengfeng Li, Junhang Luo, Bin Chen, Hui Tang, Canliang Lu, Muyan Cai, Zunfu Ke, Wei He, Yun Zheng, Dan Xie, Binkui Li, Yunfei Yuan
Purpose Early-stage hepatocellular carcinoma (E-HCC) is being diagnosed increasingly, and in one half of diagnosed patients, recurrence will develop. Thus, it is urgent to identify recurrence-related markers. We investigated the effectiveness of CpG methylation in predicting recurrence for patients with E-HCCs. Patients and Methods In total, 576 patients with E-HCC from four independent centers were sorted by three phases. In the discovery phase, 66 tumor samples were analyzed using the Illumina Methylation 450k Beadchip...
January 9, 2017: Journal of Clinical Oncology: Official Journal of the American Society of Clinical Oncology
https://www.readbyqxmd.com/read/28068089/food-targeting-geographical-origin-determination-of-hazelnuts-corylus-avellana-by-lc-qqq-ms-ms-based-targeted-metabolomics-application
#14
Sven Klockmann, Eva Reiner, Nicolas Cain, Markus Fischer
A targeted metabolomics LC-ESI-QqQ-MS application for geographical origin discrimination based on 20 non-polar key metabolites was developed, validated according to accepted guidelines and used for quantitation via stable isotope labeled internal standards in 202 raw authentic hazelnut samples from six countries (Turkey, Italy, Georgia, Spain, France and Germany) out of harvest years 2014 and 2015. Multivariate statistics were used for detection of significant variations in metabolite levels between countries and moreover, a prediction model using support vector machine classification (SVM) was calculated yielding 100% training accuracy and 97% cross-validation accuracy which was subsequently applied to 55 hazelnut samples for confectionary industry gaining up to 80% correct classifications compared to declared origin...
January 9, 2017: Journal of Agricultural and Food Chemistry
https://www.readbyqxmd.com/read/28067767/depth-errors-analysis-and-correction-for-time-of-flight-tof-cameras
#15
Ying He, Bin Liang, Yu Zou, Jin He, Jun Yang
Time-of-Flight (ToF) cameras, a technology which has developed rapidly in recent years, are 3D imaging sensors providing a depth image as well as an amplitude image with a high frame rate. As a ToF camera is limited by the imaging conditions and external environment, its captured data are always subject to certain errors. This paper analyzes the influence of typical external distractions including material, color, distance, lighting, etc. on the depth error of ToF cameras. Our experiments indicated that factors such as lighting, color, material, and distance could cause different influences on the depth error of ToF cameras...
January 5, 2017: Sensors
https://www.readbyqxmd.com/read/28066816/from-genomes-to-phenotypes-traitar-the-microbial-trait-analyzer
#16
Aaron Weimann, Kyra Mooren, Jeremy Frank, Phillip B Pope, Andreas Bremges, Alice C McHardy
The number of sequenced genomes is growing exponentially, profoundly shifting the bottleneck from data generation to genome interpretation. Traits are often used to characterize and distinguish bacteria and are likely a driving factor in microbial community composition, yet little is known about the traits of most microbes. We describe Traitar, the microbial trait analyzer, which is a fully automated software package for deriving phenotypes from a genome sequence. Traitar provides phenotype classifiers to predict 67 traits related to the use of various substrates as carbon and energy sources, oxygen requirement, morphology, antibiotic susceptibility, proteolysis, and enzymatic activities...
November 2016: MSystems
https://www.readbyqxmd.com/read/28062441/esa-ubisite-accurate-prediction-of-human-ubiquitination-sites-by-identifying-a-set-of-effective-negatives
#17
Jyun-Rong Wang, Wen-Lin Huang, Ming-Ju Tsai, Kai-Ti Hsu, Hui-Ling Huang, Shinn-Ying Ho
MOTIVATION: Numerous ubiquitination sites remain undiscovered because of the limitations of mass spectrometry-based methods. Existing prediction methods use randomly selected non-validated sites as non-ubiquitination sites to train ubiquitination site prediction models. RESULTS: We propose an evolutionary screening algorithm (ESA) to select effective negatives among non-validated sites and an ESA-based prediction method, ESA-UbiSite, to identify human ubiquitination sites...
January 6, 2017: Bioinformatics
https://www.readbyqxmd.com/read/28060917/a-novel-mouse-segmentation-method-based-on-dynamic-contrast-enhanced-micro-ct-images
#18
Dongmei Yan, Zhihong Zhang, Qingming Luo, Xiaoquan Yang
With the development of hybrid imaging scanners, micro-CT is widely used in locating abnormalities, studying drug metabolism, and providing structural priors to aid image reconstruction in functional imaging. Due to the low contrast of soft tissues, segmentation of soft tissue organs from mouse micro-CT images is a challenging problem. In this paper, we propose a mouse segmentation scheme based on dynamic contrast enhanced micro-CT images. With a homemade fast scanning micro-CT scanner, dynamic contrast enhanced images were acquired before and after injection of non-ionic iodinated contrast agents (iohexol)...
2017: PloS One
https://www.readbyqxmd.com/read/28060807/svm-and-svm-ensembles-in-breast-cancer-prediction
#19
Min-Wei Huang, Chih-Wen Chen, Wei-Chao Lin, Shih-Wen Ke, Chih-Fong Tsai
Breast cancer is an all too common disease in women, making how to effectively predict it an active research problem. A number of statistical and machine learning techniques have been employed to develop various breast cancer prediction models. Among them, support vector machines (SVM) have been shown to outperform many related techniques. To construct the SVM classifier, it is first necessary to decide the kernel function, and different kernel functions can result in different prediction performance. However, there have been very few studies focused on examining the prediction performances of SVM based on different kernel functions...
2017: PloS One
https://www.readbyqxmd.com/read/28059133/prediction-of-n-methyl-d-aspartate-receptor-glun1-ligand-binding-affinity-by-a-novel-svm-pose-svm-score-combinatorial-ensemble-docking-scheme
#20
Max K Leong, Ren-Guei Syu, Yi-Lung Ding, Ching-Feng Weng
The glycine-binding site of the N-methyl-D-aspartate receptor (NMDAR) subunit GluN1 is a potential pharmacological target for neurodegenerative disorders. A novel combinatorial ensemble docking scheme using ligand and protein conformation ensembles and customized support vector machine (SVM)-based models to select the docked pose and to predict the docking score was generated for predicting the NMDAR GluN1-ligand binding affinity. The predicted root mean square deviation (RMSD) values in pose by SVM-Pose models were found to be in good agreement with the observed values (n = 30, r(2) = 0...
January 6, 2017: Scientific Reports
keyword
keyword
6123
1
2
Fetch more papers »
Fetching more papers... Fetching...
Read by QxMD. Sign in or create an account to discover new knowledge that matter to you.
Remove bar
Read by QxMD icon Read
×

Search Tips

Use Boolean operators: AND/OR

diabetic AND foot
diabetes OR diabetic

Exclude a word using the 'minus' sign

Virchow -triad

Use Parentheses

water AND (cup OR glass)

Add an asterisk (*) at end of a word to include word stems

Neuro* will search for Neurology, Neuroscientist, Neurological, and so on

Use quotes to search for an exact phrase

"primary prevention of cancer"
(heart or cardiac or cardio*) AND arrest -"American Heart Association"