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https://www.readbyqxmd.com/read/28101760/a-cad-of-fully-automated-colonic-polyp-detection-for-contrasted-and-non-contrasted-ct-scans
#1
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
#2
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
#3
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
#4
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
#5
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
#6
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
#7
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
#8
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
#9
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
#10
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
#11
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
#12
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
https://www.readbyqxmd.com/read/28069509/controlling-the-morphology-and-outgrowth-of-nerve-and-neuroglial-cells-the-effect-of-surface-topography
#13
REVIEW
C Simitzi, A Ranella, E Stratakis
: Unlike other tissue types, like epithelial tissue, which consist of cells with a much more homogeneous structure and function, the nervous tissue spans in a complex multilayer environment whose topographical features display a large spectrum of morphologies and size scales. Traditional cell cultures, which are based on two-dimensional cell-adhesive culture dishes or coverslips, are lacking topographical cues and mainly simulate the biochemical microenvironment of the cells. With the emergence of micro- and nano-fabrication techniques new types of cell culture platforms are developed, where the effect of various topographical cues on cellular morphology, proliferation and differentiation, can be studied...
January 6, 2017: Acta Biomaterialia
https://www.readbyqxmd.com/read/28064005/three-dimensional-functional-human-neuronal-networks-in-uncompressed-low-density-electrospun-fiber-scaffolds
#14
Albin Jakobsson, Maximilian Ottosson, Marina Castro Zalis, David O'Carroll, Ulrica Englund Johansson, Fredrik Johansson
We demonstrate an artificial three-dimensional (3D) electrical active human neuronal network system, by the growth of brain neural progenitors in highly porous low density electrospun poly-ε-caprolactone (PCL) fiber scaffolds. In neuroscience research cell-based assays are important experimental instruments for studying neuronal function in health and disease. Traditional cell culture at 2D-surfaces induces abnormal cell-cell contacts and network formation. Hence, there is a tremendous need to explore in vivo-resembling 3D neural cell culture approaches...
January 4, 2017: Nanomedicine: Nanotechnology, Biology, and Medicine
https://www.readbyqxmd.com/read/28062170/an-artificial-neural-network-method-for-lumen-and-media-adventitia-border-detection-in-ivus
#15
Shengran Su, Zhenghui Hu, Qiang Lin, William Kongto Hau, Zhifan Gao, Heye Zhang
Intravascular ultrasound (IVUS) has been well recognized as one powerful imaging technique to evaluate the stenosis inside the coronary arteries. The detection of lumen border and media-adventitia (MA) border in IVUS images is the key procedure to determine the plaque burden inside the coronary arteries, but this detection could be burdensome to the doctor because of large volume of the IVUS images. In this paper, we use the artificial neural network (ANN) method as the feature learning algorithm for the detection of the lumen and MA borders in IVUS images...
November 17, 2016: Computerized Medical Imaging and Graphics: the Official Journal of the Computerized Medical Imaging Society
https://www.readbyqxmd.com/read/28056364/estimation-of-biogas-and-methane-yields-in-an-uasb-treating-potato-starch-processing-wastewater-with-backpropagation-artificial-neural-network
#16
Philip Antwi, Jianzheng Li, Portia Opoku Boadi, Jia Meng, En Shi, Kaiwen Deng, Francis Kwesi Bondinuba
Three-layered feedforward backpropagation (BP) artificial neural networks (ANN) and multiple nonlinear regression (MnLR) models were developed to estimate biogas and methane yield in an upflow anaerobic sludge blanket (UASB) reactor treating potato starch processing wastewater (PSPW). Anaerobic process parameters were optimized to identify their importance on methanation. pH, total chemical oxygen demand, ammonium, alkalinity, total Kjeldahl nitrogen, total phosphorus, volatile fatty acids and hydraulic retention time selected based on principal component analysis were used as input variables, whiles biogas and methane yield were employed as target variables...
December 16, 2016: Bioresource Technology
https://www.readbyqxmd.com/read/28055930/deep-learning-for-health-informatics
#17
Daniele Ravi, Charence Wong, Fani Deligianni, Melissa Berthelot, Javier Andreu Perez, Benny Lo, Guang-Zhong Yang
With a massive influx of multimodality data, the role of data analytics in health informatics has grown rapidly in the last decade. This has also prompted increasing interests in the generation of analytical, data driven models based on machine learning in health informatics. Deep learning, a technique with its foundation in artificial neural networks, is emerging in recent years as a powerful tool for machine learning, promising to reshape the future of artificial intelligence. Rapid improvements in computational power, fast data storage and parallelization have also contributed to the rapid uptake of the technology in addition to its predictive power and ability to generate automatically optimized high-level features and semantic interpretation from the input data...
December 29, 2016: IEEE Journal of Biomedical and Health Informatics
https://www.readbyqxmd.com/read/28054462/optimization-of-biopharmaceutical-downstream-processes-supported-by-mechanistic-models-and-artificial-neural-networks
#18
Silvia M Pirrung, Luuk A M van der Wielen, Ruud F W C Van Beckhoven, Emile J A X van de Sandt, Michel H M Eppink, Marcel Ottens
Downstream process development is a major area of importance within the field of bioengineering. During the design of such a downstream process, important decisions have to be made regarding the type of unit operations as well as their sequence and their operating conditions. Current computational approaches addressing these issues either show a high level of simplification or struggle with computational speed. Therefore, this article presents a new approach that combines detailed mechanistic models and speed-enhancing artificial neural networks...
January 5, 2017: Biotechnology Progress
https://www.readbyqxmd.com/read/28050920/elderly-fall-risk-prediction-based-on-a-physiological-profile-approach-using-artificial-neural-networks
#19
Jafar Razmara, Mohammad Hassan Zaboli
Falls play a critical role in older people's life as it is an important source of morbidity and mortality in elders. In this article, elders fall risk is predicted based on a physiological profile approach using a multilayer neural network with back-propagation learning algorithm. The personal physiological profile of 200 elders was collected through a questionnaire and used as the experimental data for learning and testing the neural network. The profile contains a series of simple factors putting elders at risk for falls such as vision abilities, muscle forces, and some other daily activities and grouped into two sets: psychological factors and public factors...
November 1, 2016: Health Informatics Journal
https://www.readbyqxmd.com/read/28050687/the-role-of-multidrug-resistance-protein-mrp-1-as-an-active-efflux-transporter-on-blood-brain-barrier-bbb-permeability
#20
Karthik Lingineni, Vilas Belekar, Sujit R Tangadpalliwar, Prabha Garg
Drugs acting on central nervous system (CNS) may take longer duration to reach the market as these compounds have a higher attrition rate in clinical trials due to the complexity of the brain, side effects, and poor blood-brain barrier (BBB) permeability compared to non-CNS-acting compounds. The roles of active efflux transporters with BBB are still unclear. The aim of the present work was to develop a predictive model for BBB permeability that includes the MRP-1 transporter, which is considered as an active efflux transporter...
January 3, 2017: Molecular Diversity
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