keyword
MENU ▼
Read by QxMD icon Read
search

svm

keyword
https://www.readbyqxmd.com/read/28335480/weighted-kernel-entropy-component-analysis-for-fault-diagnosis-of-rolling-bearings
#1
Hongdi Zhou, Tielin Shi, Guanglan Liao, Jianping Xuan, Jie Duan, Lei Su, Zhenzhi He, Wuxing Lai
This paper presents a supervised feature extraction method called weighted kernel entropy component analysis (WKECA) for fault diagnosis of rolling bearings. The method is developed based on kernel entropy component analysis (KECA) which attempts to preserve the Renyi entropy of the data set after dimension reduction. It makes full use of the labeled information and introduces a weight strategy in the feature extraction. The class-related weights are introduced to denote differences among the samples from different patterns, and genetic algorithm (GA) is implemented to seek out appropriate weights for optimizing the classification results...
March 18, 2017: Sensors
https://www.readbyqxmd.com/read/28335471/mobile-phonocardiogram-diagnosis-in-newborns-using-support-vector-machine
#2
Amir Mohammad Amiri, Mohammadreza Abtahi, Nick Constant, Kunal Mankodiya
Phonocardiogram (PCG) monitoring on newborns is one of the most important and challenging tasks in the heart assessment in the early ages of life. In this paper, we present a novel approach for cardiac monitoring applied in PCG data. This basic system coupled with denoising, segmentation, cardiac cycle selection and classification of heart sound can be used widely for a large number of the data. This paper describes the problems and additional advantages of the PCG method including the possibility of recording heart sound at home, removing unwanted noises and data reduction on a mobile device, and an intelligent system to diagnose heart diseases on the cloud server...
March 18, 2017: Healthcare (Basel, Switzerland)
https://www.readbyqxmd.com/read/28335400/online-classification-of-contaminants-based-on-multi-classification-support-vector-machine-using-conventional-water-quality-sensors
#3
Pingjie Huang, Yu Jin, Dibo Hou, Jie Yu, Dezhan Tu, Yitong Cao, Guangxin Zhang
Water quality early warning system is mainly used to detect deliberate or accidental water pollution events in water distribution systems. Identifying the types of pollutants is necessary after detecting the presence of pollutants to provide warning information about pollutant characteristics and emergency solutions. Thus, a real-time contaminant classification methodology, which uses the multi-classification support vector machine (SVM), is proposed in this study to obtain the probability for contaminants belonging to a category...
March 13, 2017: Sensors
https://www.readbyqxmd.com/read/28333956/discriminating-between-hur-and-ttp-binding-sites-using-the-k-spectrum-kernel-method
#4
Shweta Bhandare, Debra S Goldberg, Robin Dowell
BACKGROUND: The RNA binding proteins (RBPs) human antigen R (HuR) and Tristetraprolin (TTP) are known to exhibit competitive binding but have opposing effects on the bound messenger RNA (mRNA). How cells discriminate between the two proteins is an interesting problem. Machine learning approaches, such as support vector machines (SVMs), may be useful in the identification of discriminative features. However, this method has yet to be applied to studies of RNA binding protein motifs. RESULTS: Applying the k-spectrum kernel to a support vector machine (SVM), we first verified the published binding sites of both HuR and TTP...
2017: PloS One
https://www.readbyqxmd.com/read/28333592/dc-algorithm-for-extended-robust-support-vector-machine
#5
Shuhei Fujiwara, Akiko Takeda, Takafumi Kanamori
Nonconvex variants of support vector machines (SVMs) have been developed for various purposes. For example, robust SVMs attain robustness to outliers by using a nonconvex loss function, while extended [Formula: see text]-SVM (E[Formula: see text]-SVM) extends the range of the hyperparameter by introducing a nonconvex constraint. Here, we consider an extended robust support vector machine (ER-SVM), a robust variant of E[Formula: see text]-SVM. ER-SVM combines two types of nonconvexity from robust SVMs and E[Formula: see text]-SVM...
March 23, 2017: Neural Computation
https://www.readbyqxmd.com/read/28326008/disease-specific-regions-outperform-whole-brain-approaches-in-identifying-progressive-supranuclear-palsy-a-multicentric-mri-study
#6
Karsten Mueller, Robert Jech, Cecilia Bonnet, Jaroslav Tintěra, Jaromir Hanuška, Harald E Möller, Klaus Fassbender, Albert Ludolph, Jan Kassubek, Markus Otto, Evžen Růžička, Matthias L Schroeter
To identify progressive supranuclear palsy (PSP), we combined voxel-based morphometry (VBM) and support vector machine (SVM) classification using disease-specific features in multicentric magnetic resonance imaging (MRI) data. Structural brain differences were investigated at four centers between 20 patients with PSP and 20 age-matched healthy controls with T1-weighted MRI at 3T. To pave the way for future application in personalized medicine, we applied SVM classification to identify PSP on an individual level besides group analyses based on VBM...
2017: Frontiers in Neuroscience
https://www.readbyqxmd.com/read/28325450/classification-of-nervous-system-withdrawn-and-approved-drugs-with-toxprint-features-via-machine-learning-strategies
#7
Aytun Onay, Melih Onay, Osman Abul
BACKGROUND AND OBJECTIVES: Early-phase virtual screening of candidate drug molecules plays a key role in pharmaceutical industry from data mining and machine learning to prevent adverse effects of the drugs. Computational classification methods can distinguish approved drugs from withdrawn ones. We focused on 6 data sets including maximum 110 approved and 110 withdrawn drugs for all and nervous system diseases to distinguish approved drugs from withdrawn ones. METHODS: In this study, we used support vector machines (SVMs) and ensemble methods (EMs) such as boosted and bagged trees to classify drugs into approved and withdrawn categories...
April 2017: Computer Methods and Programs in Biomedicine
https://www.readbyqxmd.com/read/28324991/features-of-cerebral-oxygenation-detects-brain-injury-in-premature-infants
#8
John M O'Toole, Mmoloki Kenosi, Daragh Finn, Geraldine B Boylan, Eugene M Dempsey
Babies born prematurely can develop brain injury within days after birth. Early identification of high-risk infants enables appropriate clinical care to mitigate potential lifelong disabilities. Near infra-red spectroscopy is an established technology that can provide continuous measurements of cerebral oxygen saturation (rcSO2) over this critical period. We develop a feature set of the rcSO2 signal for the purpose of detecting brain injury. Our feature set contains amplitude, spectral, and fractal dimension features within 5 frequency bands...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28324984/prediction-method-for-intronic-alternative-polyadenylation-sites
#9
Shanxin Zhang
Alternative Polyadenylation (APA) of mRNAs has been proven as a considerable mechanism for post-transcriptional gene regulation. The interplay between Intronic APA and splicing may affect the isoforms of mRNAs. In this paper, we have found four prevalent motifs, i.e. AATAAA, TTTTTTTT, CCAGSCTGG and RGYRYRGTGG surrounding the polyadenylation sites; then we proposed a new computational method to identify the Intronic APA sites in the human genome, which is based on a Support Vector Machine (SVM) with weighted degree string kernel...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28324952/the-influence-of-the-pre-stimulation-neural-state-on-the-post-stimulation-neural-dynamics-via-distributed-microstimulation-of-the-hippocampus
#10
Mark J Connolly, Robert E Gross, Babak Mahmoudi
In this study we investigated how the neural state influences how the brain responds to electrical stimulation using a 16-channel microelectrode array with 8 stimulation and recording channels implanted in the rat hippocampus. In two experiments we identified the stimulation threshold at which the brain changes to an afterdischarge state. In one experiment a range of suprathreshold stimulations were applied, and in another the stimulation was not changed. The neural state was measured by the power spectral density prior to stimulation...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28322997/a-new-hybrid-coding-for-protein-secondary-structure-prediction-based-on-primary-structure-similarity
#11
Zhong Li, Jing Wang, Shunpu Zhang, Qifeng Zhang, Wuming Wu
The coding pattern of protein can greatly affect the prediction accuracy of protein secondary structure. In this paper, a novel hybrid coding method based on the physicochemical properties of amino acids and tendency factors is proposed for the prediction of protein secondary structure. The principal component analysis (PCA) is first applied to the physicochemical properties of amino acids to construct a 3-bit-code, and then the 3 tendency factors of amino acids are calculated to generate another 3-bit-code...
March 16, 2017: Gene
https://www.readbyqxmd.com/read/28321182/sparse-and-specific-coding-during-information-transmission-between-co-cultured-dentate-gyrus-and-ca3-hippocampal-networks
#12
Daniele Poli, Srikanth Thiagarajan, Thomas B DeMarse, Bruce C Wheeler, Gregory J Brewer
To better understand encoding and decoding of stimulus information in two specific hippocampal sub-regions, we isolated and co-cultured rat primary dentate gyrus (DG) and CA3 neurons within a two-chamber device with axonal connectivity via micro-tunnels. We tested the hypothesis that, in these engineered networks, decoding performance of stimulus site information would be more accurate when stimuli and information flow occur in anatomically correct feed-forward DG to CA3 vs. CA3 back to DG. In particular, we characterized the neural code of these sub-regions by measuring sparseness and uniqueness of the responses evoked by specific paired-pulse stimuli...
2017: Frontiers in Neural Circuits
https://www.readbyqxmd.com/read/28306716/localization-and-diagnosis-framework-for-pediatric-cataracts-based-on-slit-lamp-images-using-deep-features-of-a-convolutional-neural-network
#13
Xiyang Liu, Jiewei Jiang, Kai Zhang, Erping Long, Jiangtao Cui, Mingmin Zhu, Yingying An, Jia Zhang, Zhenzhen Liu, Zhuoling Lin, Xiaoyan Li, Jingjing Chen, Qianzhong Cao, Jing Li, Xiaohang Wu, Dongni Wang, Haotian Lin
Slit-lamp images play an essential role for diagnosis of pediatric cataracts. We present a computer vision-based framework for the automatic localization and diagnosis of slit-lamp images by identifying the lens region of interest (ROI) and employing a deep learning convolutional neural network (CNN). First, three grading degrees for slit-lamp images are proposed in conjunction with three leading ophthalmologists. The lens ROI is located in an automated manner in the original image using two successive applications of Candy detection and the Hough transform, which are cropped, resized to a fixed size and used to form pediatric cataract datasets...
2017: PloS One
https://www.readbyqxmd.com/read/28304378/generating-highly-accurate-prediction-hypotheses-through-collaborative-ensemble-learning
#14
Nino Arsov, Martin Pavlovski, Lasko Basnarkov, Ljupco Kocarev
Ensemble generation is a natural and convenient way of achieving better generalization performance of learning algorithms by gathering their predictive capabilities. Here, we nurture the idea of ensemble-based learning by combining bagging and boosting for the purpose of binary classification. Since the former improves stability through variance reduction, while the latter ameliorates overfitting, the outcome of a multi-model that combines both strives toward a comprehensive net-balancing of the bias-variance trade-off...
March 17, 2017: Scientific Reports
https://www.readbyqxmd.com/read/28300144/fast-detection-of-tobacco-mosaic-virus-infected-tobacco-using-laser-induced-breakdown-spectroscopy
#15
Jiyu Peng, Kunlin Song, Hongyan Zhu, Wenwen Kong, Fei Liu, Tingting Shen, Yong He
Tobacco mosaic virus (TMV) is one of the most devastating viruses to crops, which can cause severe production loss and affect the quality of products. In this study, we have proposed a novel approach to discriminate TMV-infected tobacco based on laser-induced breakdown spectroscopy (LIBS). Two different kinds of tobacco samples (fresh leaves and dried leaf pellets) were collected for spectral acquisition, and partial least squared discrimination analysis (PLS-DA) was used to establish classification models based on full spectrum and observed emission lines...
March 16, 2017: Scientific Reports
https://www.readbyqxmd.com/read/28294963/voxel-based-neighborhood-for-spatial-shape-pattern-classification-of-lidar-point-clouds-with-supervised-learning
#16
Victoria Plaza-Leiva, Jose Antonio Gomez-Ruiz, Anthony Mandow, Alfonso García-Cerezo
Improving the effectiveness of spatial shape features classification from 3D lidar data is very relevant because it is largely used as a fundamental step towards higher level scene understanding challenges of autonomous vehicles and terrestrial robots. In this sense, computing neighborhood for points in dense scans becomes a costly process for both training and classification. This paper proposes a new general framework for implementing and comparing different supervised learning classifiers with a simple voxel-based neighborhood computation where points in each non-overlapping voxel in a regular grid are assigned to the same class by considering features within a support region defined by the voxel itself...
March 15, 2017: Sensors
https://www.readbyqxmd.com/read/28294050/an-integrated-multi-qsar-modeling-approach-for-designing-knoevenagel-type-indoles-with-enhancing-cytotoxic-profiles
#17
Sk Abdul Amin, Nilanjan Adhikari, Tarun Jha, Shovanlal Gayen
BACKGROUND: Unconventional Knoevenagel-type indoles have been the topic of interest of many synthetic chemists because of its promising efficacy in different diseases including in cancer. OBJECTIVE: To explore the structural requirements of Knoevenagel-type cytotoxic indoles for higher efficacy. METHODS: Multi-QSAR modeling (MLR, ANN, SVM, Bayesian classification, HQSAR and Topomer CoMFA) was performed on these analogs. RESULTS: All these modeling techniques were validated individually and interpreted with the experimental SAR observations...
March 9, 2017: Current Computer-aided Drug Design
https://www.readbyqxmd.com/read/28286064/predicting-conversion-from-mci-to-ad-using-resting-state-fmri-graph-theoretical-approach-and-svm
#18
Seyed Hani Hojjati, Ata Ebrahimzadeh, Ali Khazaee, Abbas Babajani-Feremi
BACKGROUND: We investigated identifying patients with mild cognitive impairment (MCI) who progress to Alzheimer's disease (AD), MCI converter (MCI-C), from those with MCI who do not progress to AD, MCI non-converter (MCI-NC), based on resting-state fMRI (rs-fMRI). NEW METHOD: Graph theory and machine learning approach were utilized to predict progress of patients with MCI to AD using rs-fMRI. Eighteen MCI converts (average age 73.6 years; 11 male) and 62 age-matched MCI non-converters (average age 73...
March 9, 2017: Journal of Neuroscience Methods
https://www.readbyqxmd.com/read/28286029/classification-of-toxicity-effects-of-biotransformed-hepatic-drugs-using-whale-optimized-support-vector-machines
#19
Alaa Tharwat, Yasmine S Moemen, Aboul Ella Hassanien
Measuring toxicity is an important step in drug development. Nevertheless, the current experimental methods used to estimate the drug toxicity are expensive and time-consuming, indicating that they are not suitable for large-scale evaluation of drug toxicity in the early stage of drug development. Hence, there is a high demand to develop computational models that can predict the drug toxicity risks. In this study, we used a dataset that consists of 553 drugs that biotransformed in liver. The toxic effects were calculated for the current data, namely, mutagenic, tumorigenic, irritant and reproductive effect...
March 7, 2017: Journal of Biomedical Informatics
https://www.readbyqxmd.com/read/28285338/a-study-of-computer-aided-diagnosis-for-pulmonary-nodule-comparison-between-classification-accuracies-using-calculated-image-features-and-imaging-findings-annotated-by-radiologists
#20
Masami Kawagishi, Bin Chen, Daisuke Furukawa, Hiroyuki Sekiguchi, Koji Sakai, Takeshi Kubo, Masahiro Yakami, Koji Fujimoto, Ryo Sakamoto, Yutaka Emoto, Gakuto Aoyama, Yoshio Iizuka, Keita Nakagomi, Hiroyuki Yamamoto, Kaori Togashi
PURPOSE: In our previous study, we developed a computer-aided diagnosis (CADx) system using imaging findings annotated by radiologists. The system, however, requires radiologists to input many imaging findings. In order to reduce such an interaction of radiologists, we further developed a CADx system using derived imaging findings based on calculated image features, in which the system only requires few user operations. The purpose of this study is to check whether calculated image features (CFT) or derived imaging findings (DFD) can represent information in imaging findings annotated by radiologists (AFD)...
March 11, 2017: International Journal of Computer Assisted Radiology and Surgery
keyword
keyword
116917
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"