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"Artificial neural network"

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https://www.readbyqxmd.com/read/28108817/computerized-classification-of-pneumoconiosis-on-digital-chest-radiography-artificial-neural-network-with-three-stages
#1
Eiichiro Okumura, Ikuo Kawashita, Takayuki Ishida
It is difficult for radiologists to classify pneumoconiosis from category 0 to category 3 on chest radiographs. Therefore, we have developed a computer-aided diagnosis (CAD) system based on a three-stage artificial neural network (ANN) method for classification based on four texture features. The image database consists of 36 chest radiographs classified as category 0 to category 3. Regions of interest (ROIs) with a matrix size of 32 × 32 were selected from chest radiographs. We obtained a gray-level histogram, histogram of gray-level difference, gray-level run-length matrix (GLRLM) feature image, and gray-level co-occurrence matrix (GLCOM) feature image in each ROI...
January 20, 2017: Journal of Digital Imaging: the Official Journal of the Society for Computer Applications in Radiology
https://www.readbyqxmd.com/read/28108187/application-of-an-artificial-neural-network-for-evaluation-of-activity-concentration-exemption-limits-in-norm-industry
#2
Hannah Wiedner, Virginia Peyrés, Teresa Crespo, Marcos Mejuto, Eduardo García-Toraño, Franz Josef Maringer
NORM emits many different gamma energies that have to be analysed by an expert. Alternatively, artificial neural networks (ANNs) can be used. These mathematical software tools can generalize "knowledge" gained from training datasets, applying it to new problems. No expert knowledge of gamma-ray spectrometry is needed by the end-user. In this work an ANN was created that is able to decide from the raw gamma-ray spectrum if the activity concentrations in a sample are above or below the exemption limits.
December 27, 2016: Applied Radiation and Isotopes
https://www.readbyqxmd.com/read/28107913/quantitative-structure-retention-relationship-model-for-the-determination-of-naratriptan-hydrochloride-and-its-impurities-based-on-artificial-neural-networks-coupled-with-genetic-algorithm
#3
Mikołaj Mizera, Anna Krause, Przemysław Zalewski, Robert Skibiński, Judyta Cielecka-Piontek
Mathematical modeling of Quantitative Structure - Property Relationships met great interest in fields of in silico drug design and more recently, pharmaceutical analysis. In our approach we proposed automated method of creation Quantitative Structure-Retention Relationship (QSRR) for analysis of triptans, selective serotonin 5-HT1 receptor agonists used for the treatment of acute headache. The method was created using hybrid machine learning approach, namely Genetic algorithm (GA) coupled with artificial neutral networks (ANN)...
March 1, 2017: Talanta
https://www.readbyqxmd.com/read/28107205/comparison-of-linear-and-non-linear-models-for-predicting-energy-expenditure-from-raw-accelerometer-data
#4
Alexander H K Montoye, Munni Begum, Zachary Henning, Karin A Pfeiffer
This study had three purposes, all related to evaluating energy expenditure (EE) prediction accuracy from body-worn accelerometers: (1) compare linear regression to linear mixed models, (2) compare linear models to artificial neural network models, and (3) compare accuracy of accelerometers placed on the hip, thigh, and wrists. Forty individuals performed 13 activities in a 90 min semi-structured, laboratory-based protocol. Participants wore accelerometers on the right hip, right thigh, and both wrists and a portable metabolic analyzer (EE criterion)...
January 20, 2017: Physiological Measurement
https://www.readbyqxmd.com/read/28106139/spatio-temporal-tolerance-of-visuo-tactile-illusions-in-artificial-skin-by-recurrent-neural-network-with-spike-timing-dependent-plasticity
#5
Alexandre Pitti, Ganna Pugach, Philippe Gaussier, Sotaro Shimada
Perceptual illusions across multiple modalities, such as the rubber-hand illusion, show how dynamic the brain is at adapting its body image and at determining what is part of it (the self) and what is not (others). Several research studies showed that redundancy and contingency among sensory signals are essential for perception of the illusion and that a lag of 200-300 ms is the critical limit of the brain to represent one's own body. In an experimental setup with an artificial skin, we replicate the visuo-tactile illusion within artificial neural networks...
January 20, 2017: Scientific Reports
https://www.readbyqxmd.com/read/28105913/mumal2-improving-sensitivity-in-shotgun-proteomics-using-cost-sensitive-artificial-neural-networks-and-a-threshold-selector-algorithm
#6
Fabio Ribeiro Cerqueira, Adilson Mendes Ricardo, Alcione de Paiva Oliveira, Armin Graber, Christian Baumgartner
BACKGROUND: This work presents a machine learning strategy to increase sensitivity in tandem mass spectrometry (MS/MS) data analysis for peptide/protein identification. MS/MS yields thousands of spectra in a single run which are then interpreted by software. Most of these computer programs use a protein database to match peptide sequences to the observed spectra. The peptide-spectrum matches (PSMs) must also be assessed by computational tools since manual evaluation is not practicable...
December 15, 2016: BMC Bioinformatics
https://www.readbyqxmd.com/read/28105617/-establishment-of-prediction-model-of-acute-gastrointestinal-injury-classification-of-critically-ill-patients-based-on-digital-gastrointestinal-sounds-monitoring
#7
Yan Wang, Jianrong Wang, Weiwei Liu, Guangliang Zhang
OBJECTIVE: To develop the prediction model of acute gastrointestinal injury (AGI) classification of critically ill patients. METHODS: The binary channel gastrointestinal sounds (GIS) monitor system was used to gather and analyze the GIS of 60 consecutive critically ill patients who were admitted in Critical Care Medicine of PLA General Hospital from April 2015 to November 2015 (patients with chronic gastrointestinal disease or history of gastrointestinal surgery were excluded)...
January 25, 2017: Zhonghua Wei Chang Wai Ke za Zhi, Chinese Journal of Gastrointestinal Surgery
https://www.readbyqxmd.com/read/28105116/computer-assisted-quantitative-evaluation-of-bisphosphonate-treatment-for-paget-s-disease-of-bone-using-the-bone-scan-index
#8
Satoshi Nagano, Shunsuke Nakamura, Hirofumi Shimada, Masahiro Yokouchi, Takao Setoguchi, Yasuhiro Ishidou, Hiromi Sasaki, Setsuro Komiya
The purpose of the present study was to analyze the effect of treatment of Paget's disease of bone (PDB) with bone scintigraphy using a computer-assisted diagnosis system (BONENAVI) that quantitatively evaluates bone metabolism. Seven patients with PDB (three male, four female; average age, 60 years; age range, 33-80 years) underwent bone scintigraphy and measurement of serum alkaline phosphatase (ALP), bone-specific ALP (BAP), serum cross-linked N-telopeptide (NTx) of type I collagen, urinary NTx, and deoxypyridinoline (DPD) before and after bisphosphonate treatment...
December 2016: Experimental and Therapeutic Medicine
https://www.readbyqxmd.com/read/28101760/a-cad-of-fully-automated-colonic-polyp-detection-for-contrasted-and-non-contrasted-ct-scans
#9
Gökalp Tulum, Bülent Bolat, Onur Osman
PURPOSE: Computer-aided detection (CAD) systems are developed to help radiologists detect colonic polyps over CT scans. It is possible to reduce the detection time and increase the detection accuracy rates by using CAD systems. In this paper, we aimed to develop a fully integrated CAD system for automated detection of polyps that yields a high polyp detection rate with a reasonable number of false positives. METHODS: The proposed CAD system is a multistage implementation whose main components are: automatic colon segmentation, candidate detection, feature extraction and classification...
January 18, 2017: International Journal of Computer Assisted Radiology and Surgery
https://www.readbyqxmd.com/read/28100896/investigating-the-effect-of-traditional-persian-music-on-ecg-signals-in-young-women-using-wavelet-transform-and-neural-networks
#10
Behzad Abedi, Ataollah Abbasi, Atefeh Goshvarpour
OBJECTIVE: In the past few decades, several studies have reported the physiological effects of listening to music. The physiological effects of different music types on different people are different. In the present study, we aimed to examine the effects of listening to traditional Persian music on electrocardiogram (ECG) signals in young women. METHODS: Twenty-two healthy females participated in this study. ECG signals were recorded under two conditions: rest and music...
January 17, 2017: Anatolian Journal of Cardiology
https://www.readbyqxmd.com/read/28098186/a-novel-multi-target-regression-framework-for-time-series-prediction-of-drug-efficacy
#11
Haiqing Li, Wei Zhang, Ying Chen, Yumeng Guo, Guo-Zheng Li, Xiaoxin Zhu
Excavating from small samples is a challenging pharmacokinetic problem, where statistical methods can be applied. Pharmacokinetic data is special due to the small samples of high dimensionality, which makes it difficult to adopt conventional methods to predict the efficacy of traditional Chinese medicine (TCM) prescription. The main purpose of our study is to obtain some knowledge of the correlation in TCM prescription. Here, a novel method named Multi-target Regression Framework to deal with the problem of efficacy prediction is proposed...
January 18, 2017: Scientific Reports
https://www.readbyqxmd.com/read/28094340/lifetime-prediction-for-organic-coating-under-alternating-hydrostatic-pressure-by-artificial-neural-network
#12
Wenliang Tian, Fandi Meng, Li Liu, Ying Li, Fuhui Wang
A concept for prediction of organic coatings, based on the alternating hydrostatic pressure (AHP) accelerated tests, has been presented. An AHP accelerated test with different pressure values has been employed to evaluate coating degradation. And a back-propagation artificial neural network (BP-ANN) has been established to predict the service property and the service lifetime of coatings. The pressure value (P), immersion time (t) and service property (impedance modulus |Z|) are utilized as the parameters of the network...
January 17, 2017: Scientific Reports
https://www.readbyqxmd.com/read/28091786/a-new-look-at-the-drug-resistance-investigation-of-uropathogenic-e-coli-strains
#13
Wioletta Adamus-Białek, Łukasz Lechowicz, Anna B Kubiak-Szeligowska, Monika Wawszczak, Ewelina Kamińska, Magdalena Chrapek
Bacterial drug resistance and uropathogenic tract infections are among the most important issues of current medicine. Uropathogenic Escherichia coli strains are the primary factor of this issue. This article is the continuation of the previous study, where we used Kohonen relations to predict the direction of drug resistance. The characterized collection of uropathogenic E. coli strains was used for microbiological (the disc diffusion method for antimicrobial susceptibility testing), chemical (ATR/FT-IR) and mathematical (artificial neural networks, Ward's hierarchical clustering method, the analysis of distributions of inhibition zone diameters for antibiotics, Cohen's kappa measure of agreement) analysis...
January 13, 2017: Molecular Biology Reports
https://www.readbyqxmd.com/read/28090147/regression-shrinkage-and-neural-models-in-predicting-the-results-of-400-metres-hurdles-races
#14
K Przednowek, J Iskra, A Maszczyk, M Nawrocka
This study presents the application of regression shrinkage and artificial neural networks in predicting the results of 400-metres hurdles races. The regression models predict the results for suggested training loads in the selected three-month training period. The material of the research was based on training data of 21 Polish hurdlers from the Polish National Athletics Team Association. The athletes were characterized by a high level of performance. To assess the predictive ability of the constructed models a method of leave-one-out cross-validation was used...
December 2016: Biology of Sport
https://www.readbyqxmd.com/read/28089531/predicting-the-particle-size-distribution-of-eroded-sediment-using-artificial-neural-networks
#15
María Paz Lagos-Avid, Carlos A Bonilla
Water erosion causes soil degradation and nonpoint pollution. Pollutants are primarily transported on the surfaces of fine soil and sediment particles. Several soil loss models and empirical equations have been developed for the size distribution estimation of the sediment leaving the field, including the physically-based models and empirical equations. Usually, physically-based models require a large amount of data, sometimes exceeding the amount of available data in the modeled area. Conversely, empirical equations do not always predict the sediment composition associated with individual events and may require data that are not always available...
January 12, 2017: Science of the Total Environment
https://www.readbyqxmd.com/read/28086889/hybrid-brain-computer-interface-for-biomedical-cyber-physical-system-application-using-wireless-embedded-eeg-systems
#16
Rifai Chai, Ganesh R Naik, Sai Ho Ling, Hung T Nguyen
BACKGROUND: One of the key challenges of the biomedical cyber-physical system is to combine cognitive neuroscience with the integration of physical systems to assist people with disabilities. Electroencephalography (EEG) has been explored as a non-invasive method of providing assistive technology by using brain electrical signals. METHODS: This paper presents a unique prototype of a hybrid brain computer interface (BCI) which senses a combination classification of mental task, steady state visual evoked potential (SSVEP) and eyes closed detection using only two EEG channels...
January 7, 2017: Biomedical Engineering Online
https://www.readbyqxmd.com/read/28080124/statistical-learning-of-parts-and-wholes-a-neural-network-approach
#17
David C Plaut, Anna K Vande Velde
Statistical learning is often considered to be a means of discovering the units of perception, such as words and objects, and representing them as explicit "chunks." However, entities are not undifferentiated wholes but often contain parts that contribute systematically to their meanings. Studies of incidental auditory or visual statistical learning suggest that, as participants learn about wholes they become insensitive to parts embedded within them, but this seems difficult to reconcile with a broad range of findings in which parts and wholes work together to contribute to behavior...
January 12, 2017: Journal of Experimental Psychology. General
https://www.readbyqxmd.com/read/28077893/the-prediction-of-the-risk-level-of-pulmonary-embolism-and-deep-vein-thrombosis-through-artificial-neural-network
#18
Laleh Agharezaei, Zhila Agharezaei, Ali Nemati, Kambiz Bahaadinbeigy, Farshid Keynia, Mohammad Reza Baneshi, Abedin Iranpour, Moslem Agharezaei
BACKGROUND: Venous thromboembolism is a common cause of mortality among hospitalized patients and yet it is preventable through detecting the precipitating factors and a prompt diagnosis by specialists. The present study has been carried out in order to assist specialists in the diagnosis and prediction of the risk level of pulmonary embolism in patients, by means of artificial neural network. METHOD: A number of 31 risk factors have been used in this study in order to evaluate the conditions of 294 patients hospitalized in 3 educational hospitals affiliated with Kerman University of Medical Sciences...
October 2016: Acta Informatica Medica: AIM
https://www.readbyqxmd.com/read/28076681/computational-modeling-of-neurotransmitter-release-evoked-by-electrical-stimulation-non-linear-approaches-to-predicting-stimulation-evoked-dopamine-release
#19
James K Trevathan, Ali Yousefi, Hyung Ook Park, John J Bartoletta, Kip A Ludwig, Kendall H Lee, J Luis Lujan
Neurochemical changes evoked by electrical stimulation of the nervous system have been linked to both therapeutic and undesired effects of neuromodulation therapies used to treat obsessive-compulsive disorder, depression, epilepsy, Parkinson's disease, stroke, hypertension, tinnitus, and many other indications. In fact, interest in better understanding the role of neurochemical signaling in neuromodulation therapies has been a focus of recent government- and industry-sponsored programs whose ultimate goal is to usher in an era of personalized medicine by creating neuromodulation therapies that respond to real-time changes in patient status...
January 11, 2017: ACS Chemical Neuroscience
https://www.readbyqxmd.com/read/28074528/respiratory-motion-prediction-and-prospective-correction-for-free-breathing-arterial-spin-labeled-perfusion-mri-of-the-kidneys
#20
Hao Song, Dan Ruan, Wenyang Liu, V Andrew Stenger, Rolf Pohmann, Maria A Fernandez Seara, Tejas Nair, Sungkyu Jung, Jingqin Luo, Yuichi Motai, Jingfei Ma, John D Hazle, H Michael Gach
PURPOSE: Respiratory motion prediction using an artificial neural network (ANN) was integrated with pseudocontinuous arterial spin labeling (pCASL) MRI to allow free-breathing perfusion measurements in the kidney. In this study, we evaluated the performance of the ANN to accurately predict the location of the kidneys during image acquisition. METHODS: A pencil-beam navigator was integrated with a pCASL sequence to measure lung/diaphragm motion during ANN training and the pCASL transit delay...
January 11, 2017: Medical Physics
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