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Artificial neural networks

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https://www.readbyqxmd.com/read/28212422/probability-matching-in-perceptrons-effects-of-conditional-dependence-and-linear-nonseparability
#1
Michael R W Dawson, Maya Gupta
Probability matching occurs when the behavior of an agent matches the likelihood of occurrence of events in the agent's environment. For instance, when artificial neural networks match probability, the activity in their output unit equals the past probability of reward in the presence of a stimulus. Our previous research demonstrated that simple artificial neural networks (perceptrons, which consist of a set of input units directly connected to a single output unit) learn to match probability when presented different cues in isolation...
2017: PloS One
https://www.readbyqxmd.com/read/28212138/deep-learning-in-mammography-diagnostic-accuracy-of-a-multipurpose-image-analysis-software-in-the-detection-of-breast-cancer
#2
Anton S Becker, Magda Marcon, Soleen Ghafoor, Moritz C Wurnig, Thomas Frauenfelder, Andreas Boss
OBJECTIVES: The aim of this study was to evaluate the diagnostic accuracy of a multipurpose image analysis software based on deep learning with artificial neural networks for the detection of breast cancer in an independent, dual-center mammography data set. MATERIALS AND METHODS: In this retrospective, Health Insurance Portability and Accountability Act-compliant study, all patients undergoing mammography in 2012 at our institution were reviewed (n = 3228). All of their prior and follow-up mammographies from a time span of 7 years (2008-2015) were considered as a reference for clinical diagnosis...
February 16, 2017: Investigative Radiology
https://www.readbyqxmd.com/read/28212113/age-and-gender-dependency-of-physiological-networks-in-sleep
#3
Dagmar Krefting, Christoph Jansen, Thomas Penzel, Fang Han, Jan Kantelhardt
Recently, time delay stability analysis of biosignals has been successfully applied as a multivariate time series analysis method to assess the human physiological network in young adults. The degree of connectivity between different network nodes is described by the so-called link strength. Based on polysomnographic recordings (PSGs), it could be shown that the network changes with the sleep stage. Here, we apply the method to a large set of healthy controls spanning six decades of age. As it is well known, that the overall sleep architecture is dependent both on age and on gender, we particularly address the question, if these changes are also found in the network dynamics...
February 17, 2017: Physiological Measurement
https://www.readbyqxmd.com/read/28201916/artificial-neural-network-for-the-configuration-problem-in-solids
#4
Hyunjun Ji, Yousung Jung
A machine learning approach based on the artificial neural network (ANN) is applied for the configuration problem in solids. The proposed method provides a direct mapping from configuration vectors to energies. The benchmark conducted for the M1 phase of Mo-V-Te-Nb oxide showed that only a fraction of configurations needs to be calculated, thus the computational burden significantly decreased, by a factor of 20-50, with R(2) = 0.96 and MAD = 0.12 eV. It is shown that ANN can also handle the effects of geometry relaxation when properly trained, resulting in R(2) = 0...
February 14, 2017: Journal of Chemical Physics
https://www.readbyqxmd.com/read/28198674/sequence-specific-bias-correction-for-rna-seq-data-using-recurrent-neural-networks
#5
Yao-Zhong Zhang, Rui Yamaguchi, Seiya Imoto, Satoru Miyano
BACKGROUND: The recent success of deep learning techniques in machine learning and artificial intelligence has stimulated a great deal of interest among bioinformaticians, who now wish to bring the power of deep learning to bare on a host of bioinformatical problems. Deep learning is ideally suited for biological problems that require automatic or hierarchical feature representation for biological data when prior knowledge is limited. In this work, we address the sequence-specific bias correction problem for RNA-seq data redusing Recurrent Neural Networks (RNNs) to model nucleotide sequences without pre-determining sequence structures...
January 25, 2017: BMC Genomics
https://www.readbyqxmd.com/read/28196722/comparison-of-models-for-predicting-the-changes-in-phytoplankton-community-composition-in-the-receiving-water-system-of-an-inter-basin-water-transfer-project
#6
Qinghui Zeng, Yi Liu, Hongtao Zhao, Mingdong Sun, Xuyong Li
Inter-basin water transfer projects might cause complex hydro-chemical and biological variation in the receiving aquatic ecosystems. Whether machine learning models can be used to predict changes in phytoplankton community composition caused by water transfer projects have rarely been studied. In the present study, we used machine learning models to predict the total algal cell densities and changes in phytoplankton community composition in Miyun reservoir caused by the middle route of the South-to-North Water Transfer Project (SNWTP)...
February 10, 2017: Environmental Pollution
https://www.readbyqxmd.com/read/28195664/an-adaptive-model-for-rapid-and-direct-estimation-of-extravascular-extracellular-space-in-dynamic-contrast-enhanced-mri-studies
#7
Azimeh N V Dehkordi, Alireza Kamali-Asl, James R Ewing, Ning Wen, Indrin J Chetty, Hassan Bagher-Ebadian
Extravascular extracellular space (ve ) is a key parameter to characterize the tissue of cerebral tumors. This study introduces an artificial neural network (ANN) as a fast, direct, and accurate estimator of ve from a time trace of the longitudinal relaxation rate, ΔR1 (R1  = 1/T1 ), in DCE-MRI studies. Using the extended Tofts equation, a set of ΔR1 profiles was simulated in the presence of eight different signal to noise ratios. A set of gain- and noise-insensitive features was generated from the simulated ΔR1 profiles and used as the ANN training set...
February 14, 2017: NMR in Biomedicine
https://www.readbyqxmd.com/read/28194673/assessment-of-groundwater-vulnerability-using-supervised-committee-to-combine-fuzzy-logic-models
#8
Ata Allah Nadiri, Maryam Gharekhani, Rahman Khatibi, Asghar Asghari Moghaddam
Vulnerability indices of an aquifer assessed by different fuzzy logic (FL) models often give rise to differing values with no theoretical or empirical basis to establish a validated baseline or to develop a comparison basis between the modeling results and baselines, if any. Therefore, this research presents a supervised committee fuzzy logic (SCFL) method, which uses artificial neural networks to overarch and combine a selection of FL models. The indices are expressed by the widely used DRASTIC framework, which include geological, hydrological, and hydrogeological parameters often subject to uncertainty...
February 13, 2017: Environmental Science and Pollution Research International
https://www.readbyqxmd.com/read/28194106/reacog-a-minimal-cognitive-controller-based-on-recruitment-of-reactive-systems
#9
Malte Schilling, Holk Cruse
It has often been stated that for a neuronal system to become a cognitive one, it has to be large enough. In contrast, we argue that a basic property of a cognitive system, namely the ability to plan ahead, can already be fulfilled by small neuronal systems. As a proof of concept, we propose an artificial neural network, termed reaCog, that, first, is able to deal with a specific domain of behavior (six-legged-walking). Second, we show how a minor expansion of this system enables the system to plan ahead and deploy existing behavioral elements in novel contexts in order to solve current problems...
2017: Frontiers in Neurorobotics
https://www.readbyqxmd.com/read/28193201/an-artificial-neural-networks-approach-for-assessment-treatment-response-in-oncological-patients-using-pet-ct-images
#10
Mariana A Nogueira, Pedro H Abreu, Pedro Martins, Penousal Machado, Hugo Duarte, João Santos
BACKGROUND: Positron Emission Tomography - Computed Tomography (PET/CT) imaging is the basis for the evaluation of response-to-treatment of several oncological diseases. In practice, such evaluation is manually performed by specialists, which is rather complex and time-consuming. Evaluation measures have been proposed, but with questionable reliability. The usage of before and after-treatment image descriptors of the lesions for treatment response evaluation is still a territory to be explored...
February 13, 2017: BMC Medical Imaging
https://www.readbyqxmd.com/read/28189048/discovery-of-discriminatory-quality-control-markers-for-chinese-herbal-medicines-and-related-processed-products-by-combination-of-chromatographic-analysis-and-chemometrics-methods-radix-scutellariae-as-a-case-study
#11
Fei Wang, Bo Wang, Long Wang, Zi-Yue Xiong, Wen Gao, Ping Li, Hui-Jun Li
The processing procedure of traditional Chinese herbal medicines (CHMs) plays an essential role in clinical applications. However, little progress has been made on the quality control of crude and processed products. The present work, taking Radix Scutellariae (RS), wine-processed RS and carbonized RS as a typical case, developed a comprehensive strategy integrating chromatographic analysis and chemometric methods for quality evaluation and discrimination of crude RS and its processed products. Chemical fingerprints were established by high-performance liquid chromatography coupled with photodiode array detector and quadrupole time-of-flight mass spectrometry, and similarity analyses were calculated based on eleven common characteristic peaks...
February 3, 2017: Journal of Pharmaceutical and Biomedical Analysis
https://www.readbyqxmd.com/read/28185577/artificial-neural-network-classifier-predicts-neuroblastoma-patients-outcome
#12
Davide Cangelosi, Simone Pelassa, Martina Morini, Massimo Conte, Maria Carla Bosco, Alessandra Eva, Angela Rita Sementa, Luigi Varesio
BACKGROUND: More than fifty percent of neuroblastoma (NB) patients with adverse prognosis do not benefit from treatment making the identification of new potential targets mandatory. Hypoxia is a condition of low oxygen tension, occurring in poorly vascularized tissues, which activates specific genes and contributes to the acquisition of the tumor aggressive phenotype. We defined a gene expression signature (NB-hypo), which measures the hypoxic status of the neuroblastoma tumor. We aimed at developing a classifier predicting neuroblastoma patients' outcome based on the assessment of the adverse effects of tumor hypoxia on the progression of the disease...
November 8, 2016: BMC Bioinformatics
https://www.readbyqxmd.com/read/28183973/solving-the-quantum-many-body-problem-with-artificial-neural-networks
#13
Giuseppe Carleo, Matthias Troyer
The challenge posed by the many-body problem in quantum physics originates from the difficulty of describing the nontrivial correlations encoded in the exponential complexity of the many-body wave function. Here we demonstrate that systematic machine learning of the wave function can reduce this complexity to a tractable computational form for some notable cases of physical interest. We introduce a variational representation of quantum states based on artificial neural networks with a variable number of hidden neurons...
February 10, 2017: Science
https://www.readbyqxmd.com/read/28180191/doppler-ultrasonography-combined-with-transient-elastography-improves-the-non-invasive-assessment-of-fibrosis-in-patients-with-chronic-liver-diseases
#14
Tamara Alempijevic, Simon Zec, Vladimir Nikolic, Aleksandar Veljkovic, Zoran Stojanovic, Vera Matovic, Tomica Milosavljevic
AIMS: Accurate clinical assessment of liver fibrosis is essential and the aim of our study was to compare and combine hemodynamic Doppler ultrasonography, liver stiffness by transient elastography, and non-invasive serum biomarkers with the degree of fibrosis confirmed by liver biopsy, and thereby to determine the value of combining non-invasive method in the prediction significant liver fibrosis. MATERIAL AND METHODS: We included 102 patients with chronic liver disease of various etiology...
January 31, 2017: Medical Ultrasonography
https://www.readbyqxmd.com/read/28179882/connecting-artificial-brains-to-robots-in-a-comprehensive-simulation-framework-the-neurorobotics-platform
#15
Egidio Falotico, Lorenzo Vannucci, Alessandro Ambrosano, Ugo Albanese, Stefan Ulbrich, Juan Camilo Vasquez Tieck, Georg Hinkel, Jacques Kaiser, Igor Peric, Oliver Denninger, Nino Cauli, Murat Kirtay, Arne Roennau, Gudrun Klinker, Axel Von Arnim, Luc Guyot, Daniel Peppicelli, Pablo Martínez-Cañada, Eduardo Ros, Patrick Maier, Sandro Weber, Manuel Huber, David Plecher, Florian Röhrbein, Stefan Deser, Alina Roitberg, Patrick van der Smagt, Rüdiger Dillman, Paul Levi, Cecilia Laschi, Alois C Knoll, Marc-Oliver Gewaltig
Combined efforts in the fields of neuroscience, computer science, and biology allowed to design biologically realistic models of the brain based on spiking neural networks. For a proper validation of these models, an embodiment in a dynamic and rich sensory environment, where the model is exposed to a realistic sensory-motor task, is needed. Due to the complexity of these brain models that, at the current stage, cannot deal with real-time constraints, it is not possible to embed them into a real-world task...
2017: Frontiers in Neurorobotics
https://www.readbyqxmd.com/read/28178169/an-artificial-neural-network-prediction-model-of-congenital-heart-disease-based-on-risk-factors-a-hospital-based-case-control-study
#16
Huixia Li, Miyang Luo, Jianfei Zheng, Jiayou Luo, Rong Zeng, Na Feng, Qiyun Du, Junqun Fang
An artificial neural network (ANN) model was developed to predict the risks of congenital heart disease (CHD) in pregnant women.This hospital-based case-control study involved 119 CHD cases and 239 controls all recruited from birth defect surveillance hospitals in Hunan Province between July 2013 and June 2014. All subjects were interviewed face-to-face to fill in a questionnaire that covered 36 CHD-related variables. The 358 subjects were randomly divided into a training set and a testing set at the ratio of 85:15...
February 2017: Medicine (Baltimore)
https://www.readbyqxmd.com/read/28176905/effect-of-roll-compaction-on-granule-size-distribution-of-microcrystalline-cellulose-mannitol-mixtures-computational-intelligence-modeling-and-parametric-analysis
#17
Pezhman Kazemi, Mohammad Hassan Khalid, Ana Pérez Gago, Peter Kleinebudde, Renata Jachowicz, Jakub Szlęk, Aleksander Mendyk
Dry granulation using roll compaction is a typical unit operation for producing solid dosage forms in the pharmaceutical industry. Dry granulation is commonly used if the powder mixture is sensitive to heat and moisture and has poor flow properties. The output of roll compaction is compacted ribbons that exhibit different properties based on the adjusted process parameters. These ribbons are then milled into granules and finally compressed into tablets. The properties of the ribbons directly affect the granule size distribution (GSD) and the quality of final products; thus, it is imperative to study the effect of roll compaction process parameters on GSD...
2017: Drug Design, Development and Therapy
https://www.readbyqxmd.com/read/28176850/application-of-machine-learning-models-to-predict-tacrolimus-stable-dose-in-renal-transplant-recipients
#18
Jie Tang, Rong Liu, Yue-Li Zhang, Mou-Ze Liu, Yong-Fang Hu, Ming-Jie Shao, Li-Jun Zhu, Hua-Wen Xin, Gui-Wen Feng, Wen-Jun Shang, Xiang-Guang Meng, Li-Rong Zhang, Ying-Zi Ming, Wei Zhang
Tacrolimus has a narrow therapeutic window and considerable variability in clinical use. Our goal was to compare the performance of multiple linear regression (MLR) and eight machine learning techniques in pharmacogenetic algorithm-based prediction of tacrolimus stable dose (TSD) in a large Chinese cohort. A total of 1,045 renal transplant patients were recruited, 80% of which were randomly selected as the "derivation cohort" to develop dose-prediction algorithm, while the remaining 20% constituted the "validation cohort" to test the final selected algorithm...
February 8, 2017: Scientific Reports
https://www.readbyqxmd.com/read/28174616/optimal-path-finding-through-mental-exploration-based-on-neural-energy-field-gradients
#19
Yihong Wang, Rubin Wang, Yating Zhu
Rodent animal can accomplish self-locating and path-finding task by forming a cognitive map in the hippocampus representing the environment. In the classical model of the cognitive map, the system (artificial animal) needs large amounts of physical exploration to study spatial environment to solve path-finding problems, which costs too much time and energy. Although Hopfield's mental exploration model makes up for the deficiency mentioned above, the path is still not efficient enough. Moreover, his model mainly focused on the artificial neural network, and clear physiological meanings has not been addressed...
February 2017: Cognitive Neurodynamics
https://www.readbyqxmd.com/read/28174613/banknote-recognition-investigating-processing-and-cognition-framework-using-competitive-neural-network
#20
Oyebade K Oyedotun, Adnan Khashman
Humans are apt at recognizing patterns and discovering even abstract features which are sometimes embedded therein. Our ability to use the banknotes in circulation for business transactions lies in the effortlessness with which we can recognize the different banknote denominations after seeing them over a period of time. More significant is that we can usually recognize these banknote denominations irrespective of what parts of the banknotes are exposed to us visually. Furthermore, our recognition ability is largely unaffected even when these banknotes are partially occluded...
February 2017: Cognitive Neurodynamics
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