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https://www.readbyqxmd.com/read/29147867/population-structure-of-candida-parapsilosis-no-genetic-difference-between-french-and-urugayan-isolates-using-microsatellite-length-polymorphism
#1
Marie Desnos-Ollivier, Victoria Bórmida, Philippe Poirier, Céline Nourrisson, Dinorah Pan, Stéphane Bretagne, Andrès Puime, Françoise Dromer
Candida parapsilosis is a human commensal yeast, frequently involved in infection worldwide and especially in neonates. It is the second species responsible for bloodstream infections in Uruguay and the third species in France. We were interested in knowing whether the population structure of isolates responsible for candidemia in France and in Uruguay was different. Genotyping methods based on microsatellite length polymorphism (MLP) have been described and are especially used for investigation of local outbreaks...
November 16, 2017: Mycopathologia
https://www.readbyqxmd.com/read/29127801/the-potential-of-chironomid-larvae-based-metrics-in-the-bioassessment-of-non-wadeable-rivers
#2
Djuradj Milošević, Dejan Mančev, Dubravka Čerba, Milica Stojković Piperac, Nataša Popović, Ana Atanacković, Jelena Đuknić, Vladica Simić, Momir Paunović
The chironomid community in non-wadeable lotic systems was tested as a source of information in the construction of biological metrics which could be used into the bioassessment protocols of large rivers. In order to achieve this, we simultaneously patterned the chironomid community structure and environmental factors along the catchment of the Danube and Sava River. The Self organizing map (SOM) recognized and visualized three different structural types of chironomid community for different environmental properties, described by means of 7 significant abiotic factors (a multi-stressor gradient)...
November 9, 2017: Science of the Total Environment
https://www.readbyqxmd.com/read/29113322/artificial-neural-network-models-for-early-diagnosis-of-hepatocellular-carcinoma-using-serum-levels-of-%C3%AE-fetoprotein-%C3%AE-fetoprotein-l3-des-%C3%AE-carboxy-prothrombin-and-golgi-protein-73
#3
Bo Li, Boan Li, Tongsheng Guo, Zhiqiang Sun, Xiaohan Li, Xiaoxi Li, Lin Chen, Jing Zhao, Yuanli Mao
More than 70% of hepatocellular carcinoma (HCC) cases develop as a consequence of liver cirrhosis (LC). Here we have evaluated the diagnostic potential of four serum biomarkers, and developed models for HCC diagnosis and differentiation from LC patients. Serum levels of α-fetoprotein (AFP), AFP-L3, des-γ-carboxy prothrombin (DCP), and Golgi protein 73 (GP73) were analyzed in 114 advanced HCC patients, 81 early stage HCC patients, and 152 LC patients. Multilayer perceptron (MLP) and radial basis function (RBF) neural networks were used to construct the diagnostic models...
October 6, 2017: Oncotarget
https://www.readbyqxmd.com/read/29080819/isolation-purification-and-antioxidant-activity-of-polysaccharides-from-the-leaves-of-maca-lepidium-meyenii
#4
Kang Caicai, Hao Limin, Zhang Liming, Zheng Zhiqiang, Yang Yongwu
Two fractions of polysaccharides (MLP-1 and MLP-2) were extracted from the leaves of maca (Lepidium Meyenii Walp.) by water, and purified using DEAE-52 ion exchange resin and sephadex G-200 clumns chromatography. An investigation was carried out for their structural characterization and antioxidant activity in vitro. The results indicated that MLP-1 was mainly composed of ribose, rhamnose, arabinose, xylose, mannose, glucose and galactose, with the molar ratio of 0.12:0.32:1.50:0.32:1.03:1.00:0.93; the MLP-2 was a homopolysaccharide composed of glucose...
October 25, 2017: International Journal of Biological Macromolecules
https://www.readbyqxmd.com/read/29065626/hybrid-disease-diagnosis-using-multiobjective-optimization-with-evolutionary-parameter-optimization
#5
MadhuSudana Rao Nalluri, Kannan K, Manisha M, Diptendu Sinha Roy
With the widespread adoption of e-Healthcare and telemedicine applications, accurate, intelligent disease diagnosis systems have been profoundly coveted. In recent years, numerous individual machine learning-based classifiers have been proposed and tested, and the fact that a single classifier cannot effectively classify and diagnose all diseases has been almost accorded with. This has seen a number of recent research attempts to arrive at a consensus using ensemble classification techniques. In this paper, a hybrid system is proposed to diagnose ailments using optimizing individual classifier parameters for two classifier techniques, namely, support vector machine (SVM) and multilayer perceptron (MLP) technique...
2017: Journal of Healthcare Engineering
https://www.readbyqxmd.com/read/29064781/dynamics-of-learning-in-mlp-natural-gradient-and-singularity-revisited
#6
Shun-Ichi Amari, Tomoko Ozeki, Ryo Karakida, Yuki Yoshida, Masato Okada
The dynamics of supervised learning play a main role in deep learning, which takes place in the parameter space of a multilayer perceptron (MLP). We review the history of supervised stochastic gradient learning, focusing on its singular structure and natural gradient. The parameter space includes singular regions in which parameters are not identifiable. One of our results is a full exploration of the dynamical behaviors of stochastic gradient learning in an elementary singular network. The bad news is its pathological nature, in which part of the singular region becomes an attractor and another part a repulser at the same time, forming a Milnor attractor...
October 24, 2017: Neural Computation
https://www.readbyqxmd.com/read/29060711/a-bayesian-neural-network-approach-to-compare-the-spectral-information-from-nasal-pressure-and-thermistor-airflow-in-the-automatic-sleep-apnea-severity-estimation
#7
Gonzalo C Gutierrez-Tobal, Julio de Frutos, Daniel Alvarez, Fernando Vaquerizo-Villar, Veronica Barroso-Garcia, Andrea Crespo, Felix Del Campo, Roberto Hornero
In the sleep apnea-hypopnea syndrome (SAHS) context, airflow signal plays a key role for the simplification of the diagnostic process. It is measured during the standard diagnostic test by the acquisition of two simultaneous sensors: a nasal prong pressure (NPP) and a thermistor (TH). The current study focuses on the comparison of their spectral content to help in the automatic SAHS-severity estimation. The spectral analysis of 315 NPP and corresponding TH recordings is firstly proposed to characterize the conventional band of interest for SAHS (0...
July 2017: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/29060691/wrapper-method-for-feature-selection-to-classify-cardiac-arrhythmia
#8
Anam Mustaqeem, Syed Muhammad Anwar, Muhammad Majid, Abdul Rashid Khan
Efficient monitoring of cardiac patients can save tremendous amount of lives. Cardiac disease prediction and classification has gained utmost significance in this regard during the past few years. This paper presents a predictive model for classification of arrhythmias. The model works by selecting best features using wrapper algorithm around random forest, followed by implementing various machine learning classifiers on the selected features. Cardiac arrhythmia dataset from University of California, Irvine (UCI) machine learning repository has been used for the experimental purpose...
July 2017: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/29060498/pca-mlp-svm-distinction-of-salivary-raman-spectra-of-dengue-fever-infection
#9
A R M Radzol, Khuan Y Lee, W Mansor, P S Wong, I Looi
Dengue fever (DF) is a disease of major concern caused by flavivirus infection. Delayed diagnosis leads to severe stages, which could be deadly. Of recent, non-structural protein (NS1) has been acknowledged as a biomarker, alternative to immunoglobulins for early detection of dengue in blood. Further, non-invasive detection of NS1 in saliva makes the approach more appealing. However, since its concentration in saliva is less than blood, a sensitive and specific technique, Surface Enhanced Raman Spectroscopy (SERS), is employed...
July 2017: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/29059051/extension-of-the-fermi-eyges-most-likely-path-in-heterogeneous-medium-with-prior-knowledge-information
#10
Charles-Antoine Collins-Fekete, Esther Bär, Lennart Volz, Hugo Bouchard, Luc Beaulieu, Joao Seco
Particle imaging suffers from poor spatial resolution due to the multiple Coulomb scattering deflections undergone by the particles throughout their path. To account for these deflections, a most-likely path (MLP) formalism was developed based on a Bayesian adaption of the Fermi-Eyges theory. Previous work calculated the MLP formalism in a homogeneous water medium as an initial estimate. However, this potentially reduces the accuracy of the MLP estimate as well as the achievable resolution of the subsequent tomographic reconstruction...
October 23, 2017: Physics in Medicine and Biology
https://www.readbyqxmd.com/read/29054781/superselective-thalamotomy-in-the-most-lateral-part-of-the-ventralis-intermedius-nucleus-for-controlling-essential-and-parkinsonian-tremor
#11
Masafumi Hirato, Takaaki Miyagishima, Akio Takahashi, Yuhei Yoshimoto
OBJECTIVE: The minimum and essential thalamic areas for reducing tremor were investigated in cases treated by superselective thalamotomy in the most lateral part of ventralis intermedius nucleus (mlp-VIM). METHODS: Stereotactic superselective VIM thalamotomy with depth microrecording was performed in 21 patients with essential tremor (ET) and 15 patients with tremor-dominant Parkinson's disease (PD). A very small and narrow (axial plane) therapeutic lesion was formed as a square on the sagittal plane and inverse V on the axial plane in the mlp-VIM, which covered the kinesthetic response area topographically related to tremor...
October 17, 2017: World Neurosurgery
https://www.readbyqxmd.com/read/29048052/convolutional-neural-network-based-data-page-classification-for-holographic-memory
#12
Tomoyoshi Shimobaba, Naoki Kuwata, Mizuha Homma, Takayuki Takahashi, Yuki Nagahama, Marie Sano, Satoki Hasegawa, Ryuji Hirayama, Takashi Kakue, Atsushi Shiraki, Naoki Takada, Tomoyoshi Ito
We propose a deep-learning-based classification of data pages used in holographic memory. We numerically investigated the classification performance of a conventional multilayer perceptron (MLP) and a deep neural network, under the condition that reconstructed page data are contaminated by some noise and are randomly laterally shifted. When data pages are randomly laterally shifted, the MLP was found to have a classification accuracy of 93.02%, whereas the deep neural network was able to classify data pages at an accuracy of 99...
September 10, 2017: Applied Optics
https://www.readbyqxmd.com/read/29032311/a-hybrid-wavelet-de-noising-and-rank-set-pair-analysis-approach-for-forecasting-hydro-meteorological-time-series
#13
Dong Wang, Alistair G Borthwick, Handan He, Yuankun Wang, Jieyu Zhu, Yuan Lu, Pengcheng Xu, Xiankui Zeng, Jichun Wu, Lachun Wang, Xinqing Zou, Jiufu Liu, Ying Zou, Ruimin He
Accurate, fast forecasting of hydro-meteorological time series is presently a major challenge in drought and flood mitigation. This paper proposes a hybrid approach, wavelet de-noising (WD) and Rank-Set Pair Analysis (RSPA), that takes full advantage of a combination of the two approaches to improve forecasts of hydro-meteorological time series. WD allows decomposition and reconstruction of a time series by the wavelet transform, and hence separation of the noise from the original series. RSPA, a more reliable and efficient version of Set Pair Analysis, is integrated with WD to form the hybrid WD-RSPA approach...
October 12, 2017: Environmental Research
https://www.readbyqxmd.com/read/29019957/application-of-multilayer-perceptron-with-automatic-relevance-determination-on-weed-mapping-using-uav-multispectral-imagery
#14
Afroditi A Tamouridou, Thomas K Alexandridis, Xanthoula E Pantazi, Anastasia L Lagopodi, Javid Kashefi, Dimitris Kasampalis, Georgios Kontouris, Dimitrios Moshou
Remote sensing techniques are routinely used in plant species discrimination and of weed mapping. In the presented work, successful Silybum marianum detection and mapping using multilayer neural networks is demonstrated. A multispectral camera (green-red-near infrared) attached on a fixed wing unmanned aerial vehicle (UAV) was utilized for the acquisition of high-resolution images (0.1 m resolution). The Multilayer Perceptron with Automatic Relevance Determination (MLP-ARD) was used to identify the S. marianum among other vegetation, mostly Avena sterilis L...
October 11, 2017: Sensors
https://www.readbyqxmd.com/read/28982076/river-suspended-sediment-modelling-using-the-cart-model-a-comparative-study-of-machine-learning-techniques
#15
Bahram Choubin, Hamid Darabi, Omid Rahmati, Farzaneh Sajedi-Hosseini, Bjørn Kløve
Suspended sediment load (SSL) modelling is an important issue in integrated environmental and water resources management, as sediment affects water quality and aquatic habitats. Although classification and regression tree (CART) algorithms have been applied successfully to ecological and geomorphological modelling, their applicability to SSL estimation in rivers has not yet been investigated. In this study, we evaluated use of a CART model to estimate SSL based on hydro-meteorological data. We also compared the accuracy of the CART model with that of the four most commonly used models for time series modelling of SSL, i...
February 15, 2018: Science of the Total Environment
https://www.readbyqxmd.com/read/28971260/new-consensus-multivariate-models-based-on-pls-and-ann-studies-of-sigma-1-receptor-antagonists
#16
Aline A Oliveira, Célio F Lipinski, Estevão B Pereira, Kathia M Honorio, Patrícia R Oliveira, Karen C Weber, Roseli A F Romero, Alexsandro G de Sousa, Albérico B F da Silva
The treatment of neuropathic pain is very complex and there are few drugs approved for this purpose. Among the studied compounds in the literature, sigma-1 receptor antagonists have shown to be promising. In order to develop QSAR studies applied to the compounds of 1-arylpyrazole derivatives, multivariate analyses have been performed in this work using partial least square (PLS) and artificial neural network (ANN) methods. A PLS model has been obtained and validated with 45 compounds in the training set and 13 compounds in the test set (r(2)training = 0...
October 2, 2017: Journal of Molecular Modeling
https://www.readbyqxmd.com/read/28959387/classification-models-to-predict-survival-of-kidney-transplant-recipients-using-two-intelligent-techniques-of-data-mining-and-logistic-regression
#17
M Nematollahi, R Akbari, S Nikeghbalian, C Salehnasab
Kidney transplantation is the treatment of choice for patients with end-stage renal disease (ESRD). Prediction of the transplant survival is of paramount importance. The objective of this study was to develop a model for predicting survival in kidney transplant recipients. In a cross-sectional study, 717 patients with ESRD admitted to Nemazee Hospital during 2008-2012 for renal transplantation were studied and the transplant survival was predicted for 5 years. The multilayer perceptron of artificial neural networks (MLP-ANN), logistic regression (LR), Support Vector Machine (SVM), and evaluation tools were used to verify the determinant models of the predictions and determine the independent predictors...
2017: International Journal of Organ Transplantation Medicine
https://www.readbyqxmd.com/read/28956856/towards-a-continuous-biometric-system-based-on-ecg-signals-acquired-on-the-steering-wheel
#18
João Ribeiro Pinto, Jaime S Cardoso, André Lourenço, Carlos Carreiras
Electrocardiogram signals acquired through a steering wheel could be the key to seamless, highly comfortable, and continuous human recognition in driving settings. This paper focuses on the enhancement of the unprecedented lesser quality of such signals, through the combination of Savitzky-Golay and moving average filters, followed by outlier detection and removal based on normalised cross-correlation and clustering, which was able to render ensemble heartbeats of significantly higher quality. Discrete Cosine Transform (DCT) and Haar transform features were extracted and fed to decision methods based on Support Vector Machines (SVM), k-Nearest Neighbours (kNN), Multilayer Perceptrons (MLP), and Gaussian Mixture Models - Universal Background Models (GMM-UBM) classifiers, for both identification and authentication tasks...
September 28, 2017: Sensors
https://www.readbyqxmd.com/read/28948480/delineation-of-the-ischemic-stroke-lesion-based-on-watershed-and-relative-fuzzy-connectedness-in-brain-mri
#19
Asit Subudhi, Subhranshu Jena, Sukanta Sabut
Precise segmentation of stroke lesions from brain magnetic resonance (MR) images poses a challenging task in automated diagnosis. In this paper, we proposed a new method called watershed-based lesion segmentation algorithm (WLSA), which is a novel intensity-based segmentation technique used to delineate infarct lesion in diffusion-weighted imaging (DWI) MR images of the brain. The algorithm was tested on a series of 142 real-time images collected from different stroke patients reported at IMS and SUM Hospital...
September 26, 2017: Medical & Biological Engineering & Computing
https://www.readbyqxmd.com/read/28944971/a-parallel-mr-imaging-method-using-multilayer-perceptron
#20
Kinam Kwon, Dongchan Kim, HyunWook Park
PURPOSE: To reconstruct MR images from subsampled data, we propose a fast reconstruction method using the multilayer perceptron (MLP) algorithm. METHODS AND MATERIALS: We applied MLP to reduce aliasing artifacts generated by subsampling in k-space. The MLP is learned from training data to map aliased input images into desired alias-free images. The input of the MLP is all voxels in the aliased lines of multi-channel real and imaginary images from the subsampled k-space data, and the desired output is all voxels in the corresponding alias-free line of the root-sum-of-squares of multi-channel images from fully-sampled k-space data...
September 25, 2017: Medical Physics
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