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https://www.readbyqxmd.com/read/28230712/updating-evidence-for-using-hypothermia-in-pediatric-severe-traumatic-brain-injury-conventional-and-bayesian-meta-analytic-perspectives
#1
Robert C Tasker, Frederick W Vonberg, Elizabeth D Ulano, Alireza Akhondi-Asl
OBJECTIVE: To evaluate clinical trials of hypothermia management on outcome in pediatric patients with severe traumatic brain injury using conventional and Bayesian meta-analyses. DATA SOURCES: Screening of PubMed and other databases to identify randomized controlled trials of hypothermia for pediatric severe traumatic brain injury published before September 2016. STUDY SELECTION: Four investigators assessed and reviewed randomized controlled trial data...
February 20, 2017: Pediatric Critical Care Medicine
https://www.readbyqxmd.com/read/28230525/inference-and-forecast-of-h7n9-influenza-in-china-2013-to-2015
#2
Ruiyun Li, Yuqi Bai, Alex Heaney, Sasikiran Kandula, Jun Cai, Xuyi Zhao, Bing Xu, Jeffrey Shaman
The recent emergence of A(H7N9) avian influenza poses a significant challenge to public health in China and around the world; however, understanding of the transmission dynamics and progression of influenza A(H7N9) infection in domestic poultry, as well as spillover transmission to humans, remains limited. Here, we develop a mathematical model-Bayesian inference system which combines a simple epidemic model and data assimilation method, and use it in conjunction with data on observed human influenza A(H7N9) cases from 19 February 2013 to 19 September 2015 to estimate key epidemiological parameters and to forecast infection in both poultry and humans...
February 16, 2017: Euro Surveillance: Bulletin Européen sur les Maladies Transmissibles, European Communicable Disease Bulletin
https://www.readbyqxmd.com/read/28228750/evolutionary-roots-and-diversification-of-the-genus-aeromonas
#3
Ariadna Sanglas, Vicenta Albarral, Maribel Farfán, J G Lorén, M C Fusté
Despite the importance of diversification rates in the study of prokaryote evolution, they have not been quantitatively assessed for the majority of microorganism taxa. The investigation of evolutionary patterns in prokaryotes constitutes a challenge due to a very scarce fossil record, limited morphological differentiation and frequently complex taxonomic relationships, which make even species recognition difficult. Although the speciation models and speciation rates in eukaryotes have traditionally been established by analyzing the fossil record data, this is frequently incomplete, and not always available...
2017: Frontiers in Microbiology
https://www.readbyqxmd.com/read/28228504/the-dynamics-of-gastric-emptying-and-self-reported-feelings-of-satiation-are-better-predictors-than-gastrointestinal-hormones-of-the-effects-of-lipid-emulsion-structure-on-fat-digestion-in-healthy-adults-a-bayesian-inference-approach
#4
Andreas Steingoetter, Simon Buetikofer, Jelena Curcic, Dieter Menne, Jens F Rehfeld, Michael Fried, Werner Schwizer, Tim J Wooster
Background: Limited information exists on the relation between fat emulsion structure and its effect on the release of gastrointestinal hormones and feelings of satiation.Objective: We investigated the impact of fat emulsion droplet size, gravitational and acid stability, and redispersibility on gastrointestinal responses and sought to deduce the relative importance of the hormones ghrelin, cholecystokinin, glucagon-like peptide-1, and peptide YY (PYY) in controlling fat emptying and related satiation.Methods: Within a randomized, double-blind, 4-armed crossover study, an extensive data set was generated by MRI of gastric function, analysis of hormone profiles, and ratings of satiation in healthy participants [10 women and 7 men with a mean ± SD age of 25 ± 7 y and body mass index (in kg/m(2)) of 22 ± 1] after intake of 4 different fat emulsions...
February 22, 2017: Journal of Nutrition
https://www.readbyqxmd.com/read/28228094/sfreemap-a-simulation-free-tool-for-stochastic-mapping
#5
Diego Pasqualin, Marcos Barbeitos, Fabiano Silva
BACKGROUND: Stochastic mapping is frequently used in comparative biology to simulate character evolution, enabling the probabilistic computation of statistics such as number of state transitions along a tree and distribution of states in its internal nodes. Common implementations rely on Continuous-time Markov Chain simulations whose parameters are difficult to adjust and subjected to inherent inaccuracy. Thus, researchers must run a large number of simulations in order to obtain adequate estimates...
February 22, 2017: BMC Bioinformatics
https://www.readbyqxmd.com/read/28227709/bayesian-gaussian-processes-for-identifying-the-deteriorating-patient
#6
Glen Wright Colopy, Marco A F Pimentel, Stephen J Roberts, David A Clifton, Glen Wright Colopy, Marco A F Pimentel, Stephen J Roberts, David A Clifton, Glen Wright Colopy, Marco A F Pimentel, Stephen J Roberts, David A Clifton
The step-down unit (SDU) is a high-acuity hospital environment, to which patients may be sent after discharge from the intensive care unit (ICU). About 1- in-7 patients will deteriorate in the SDU and require emergency readmission to the ICU. Upon readmission, these patients experience significantly higher mortality risks and lengths of stay. Gaussian process regression (GPR) models are proposed as a flexible, principled, probabilistic method to address the clinical need to monitor continuously patient time-series of vital signs acquired in the SDU...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227700/prediction-of-oral-cancer-recurrence-using-dynamic-bayesian-networks
#7
Konstantina Kourou, George Rigas, Konstantinos P Exarchos, Costas Papaloukas, Dimitrios I Fotiadis, Konstantina Kourou, George Rigas, Konstantinos P Exarchos, Costas Papaloukas, Dimitrios I Fotiadis, George Rigas, Konstantinos P Exarchos, Dimitrios I Fotiadis, Costas Papaloukas, Konstantina Kourou
We propose a methodology for predicting oral cancer recurrence using Dynamic Bayesian Networks. The methodology takes into consideration time series gene expression data collected at the follow-up study of patients that had or had not suffered a disease relapse. Based on that knowledge, our aim is to infer the corresponding dynamic Bayesian networks and subsequently conjecture about the causal relationships among genes within the same time-slice and between consecutive time-slices. Moreover, the proposed methodology aims to (i) assess the prognosis of patients regarding oral cancer recurrence and at the same time, (ii) provide important information about the underlying biological processes of the disease...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227550/classification-of-eeg-based-mental-fatigue-using-principal-component-analysis-and-bayesian-neural-network
#8
Rifai Chai, Yvonne Tran, Ganesh R Naik, Tuan N Nguyen, Sai Ho Ling, Ashley Craig, Hung T Nguyen, Rifai Chai, Yvonne Tran, Ganesh R Naik, Tuan N Nguyen, Sai Ho Ling, Ashley Craig, Hung T Nguyen, Ashley Craig, Tuan N Nguyen, Sai Ho Ling, Hung T Nguyen, Yvonne Tran, Ganesh R Naik, Rifai Chai
This paper presents an electroencephalography (EEG) based-classification of between pre- and post-mental load tasks for mental fatigue detection from 65 healthy participants. During the data collection, eye closed and eye open tasks were collected before and after conducting the mental load tasks. For the computational intelligence, the system uses the combination of principal component analysis (PCA) as the dimension reduction method of the original 26 channels of EEG data, power spectral density (PSD) as feature extractor and Bayesian neural network (BNN) as classifier...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28226784/parameter-estimation-for-gene-regulatory-networks-a-two-stage-mcmc-bayesian-approach
#9
Niannan Xue, Wei Pan, Yike Guo, Niannan Xue, Wei Pan, Yike Guo, Wei Pan, Yike Guo, Niannan Xue
Genetic regulatory networks have emerged as a useful way to elucidate the biochemical pathways for biological functions. Yet, determination of the exact parametric forms for these models remain a major challenge. In this paper, we present a novel computational approach implemented in C++ to solve this inverse problem. This takes the form of an optimization stage first after which Bayesian filtering takes place. The key advantage of such a flexible, general and robust approach is that it provides us with a joint probability distribution of the model parameters instead of single estimates, which we can propagate to final predictions...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28226754/pixel-based-skin-segmentation-in-psoriasis-images
#10
Y George, M Aldeen, R Garnavi, Y George, M Aldeen, R Garnavi, M Aldeen, Y George, R Garnavi
In this paper, we present a detailed comparison study of skin segmentation methods for psoriasis images. Different techniques are modified and then applied to a set of psoriasis images acquired from the Royal Melbourne Hospital, Melbourne, Australia, with aim of finding the best technique suited for application to psoriasis images. We investigate the effect of different colour transformations on skin detection performance. In this respect, explicit skin thresholding is evaluated with three different decision boundaries (CbCr, HS and rgHSV)...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28226714/a-unified-bayesian-based-compensated-magnetic-resonance-imaging
#11
Ameneh Boroomand, Edward Li, Mohammad Javad Shafiee, Masoom A Haider, Farzad Khalvati, Alexander Wong, Ameneh Boroomand, Edward Li, Mohammad Javad Shafiee, Masoom A Haider, Farzad Khalvati, Alexander Wong, Alexander Wong, Mohammad Javad Shafiee, Edward Li, Masoom A Haider, Ameneh Boroomand, Farzad Khalvati
Magnetic resonance (MR) images of higher quality is demanded for helping with more accurate and earlier diagnosis of different diseases. The overall quality of MR images is limited due to the existence of different degradation factors such as (1) MR aberrations due to intrinsic properties of the MR scanner, (2) magnetic field inhomogeneity, and (3) inherent MRI noise. Correcting each MRI degradation factor could be solely useful for the quality enhancement of MR imaging with a limited impact. Here, we propose a unified Bayesian based compensated MR imaging (CMRI) system which jointly corrects for the different aforementioned MR aberrations as well as MR noise and hence generates compensated MR (CMR) images with a higher quality...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28226543/development-of-a-novel-probabilistic-algorithm-for-localization-of-rotors-during-atrial-fibrillation
#12
Prasanth Ganesan, Anthony Salmin, Elizabeth M Cherry, Behnaz Ghoraani, Prasanth Ganesan, Anthony Salmin, Elizabeth M Cherry, Behnaz Ghoraani, Elizabeth M Cherry, Prasanth Ganesan, Behnaz Ghoraani, Anthony Salmin
Atrial fibrillation (AF) is an irregular heart rhythm that can lead to stroke and other heart-related complications. Catheter ablation has been commonly used to destroy triggering sources of AF in the atria and consequently terminate the arrhythmia. However, efficient and accurate localization of the AF sustaining sources known as rotors is a major challenge in catheter ablation. In this paper, we developed a novel probabilistic algorithm that can adaptively guide a Lasso diagnostic catheter to locate the center of a rotor...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28226531/bayesian-deconvolution-of-scanning-electron-microscopy-images-using-point-spread-function-estimation-and-non-local-regularization
#13
Joris Roels, Jan Aelterman, Jonas De Vylder, Hiep Luong, Yvan Saeys, Wilfried Philips, Joris Roels, Jan Aelterman, Jonas De Vylder, Hiep Luong, Yvan Saeys, Wilfried Philips, Hiep Luong, Wilfried Philips, Jan Aelterman, Jonas De Vylder, Yvan Saeys, Joris Roels
Microscopy is one of the most essential imaging techniques in life sciences. High-quality images are required in order to solve (potentially life-saving) biomedical research problems. Many microscopy techniques do not achieve sufficient resolution for these purposes, being limited by physical diffraction and hardware deficiencies. Electron microscopy addresses optical diffraction by measuring emitted or transmitted electrons instead of photons, yielding nanometer resolution. Despite pushing back the diffraction limit, blur should still be taken into account because of practical hardware imperfections and remaining electron diffraction...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28226392/bayesian-semiparametric-variable-selection-with-applications-to-periodontal-data
#14
Bo Cai, Dipankar Bandyopadhyay
A normality assumption is typically adopted for the random effects in a clustered or longitudinal data analysis using a linear mixed model. However, such an assumption is not always realistic, and it may lead to potential biases of the estimates, especially when variable selection is taken into account. Furthermore, flexibility of nonparametric assumptions (e.g., Dirichlet process) on these random effects may potentially cause centering problems, leading to difficulty of interpretation of fixed effects and variable selection...
February 22, 2017: Statistics in Medicine
https://www.readbyqxmd.com/read/28226298/the-effect-of-muscle-fatigue-and-low-back-pain-on-lumbar-movement-variability-and-complexity
#15
C M Bauer, F M Rast, M J Ernst, A Meichtry, J Kool, S M Rissanen, J H Suni, M Kankaanpää
INTRODUCTION: Changes in movement variability and complexity may reflect an adaptation strategy to fatigue. One unresolved question is whether this adaptation is hampered by the presence of low back pain (LBP). This study investigated if changes in movement variability and complexity after fatigue are influenced by the presence of LBP. It is hypothesised that pain free people and people suffering from LBP differ in their response to fatigue. METHODS: The effect of an isometric endurance test on lumbar movement was tested in 27 pain free participants and 59 participants suffering from LBP...
February 13, 2017: Journal of Electromyography and Kinesiology
https://www.readbyqxmd.com/read/28225816/bayesian-prediction-of-placebo-analgesia-in-an-instrumental-learning-model
#16
Won-Mo Jung, Ye-Seul Lee, Christian Wallraven, Younbyoung Chae
Placebo analgesia can be primarily explained by the Pavlovian conditioning paradigm in which a passively applied cue becomes associated with less pain. In contrast, instrumental conditioning employs an active paradigm that might be more similar to clinical settings. In the present study, an instrumental conditioning paradigm involving a modified trust game in a simulated clinical situation was used to induce placebo analgesia. Additionally, Bayesian modeling was applied to predict the placebo responses of individuals based on their choices...
2017: PloS One
https://www.readbyqxmd.com/read/28225771/the-phylodynamics-of-the-rabies-virus-in-the-russian-federation
#17
Andrei A Deviatkin, Alexander N Lukashev, Elena M Poleshchuk, Vladimir G Dedkov, Sergey E Tkachev, Gennadiy N Sidorov, Galina G Karganova, Irina V Galkina, Mikhail Yu Shchelkanov, German A Shipulin
Near complete rabies virus N gene sequences (1,110 nt) were determined for 82 isolates obtained from different regions of Russia between 2008 and 2016. These sequences were analyzed together with 108 representative GenBank sequences from 1977-2016 using the Bayesian coalescent approach. The timing of the major evolutionary events was estimated. Most of the isolates represented the steppe rabies virus group C, which was found over a vast geographic region from Central Russia to Mongolia and split into three groups (C0-C2) with discrete geographic prevalence...
2017: PloS One
https://www.readbyqxmd.com/read/28225651/robotic-surgery-a-solution-in-search-of-a-problem-a-bayesian-analysis-of-343-robotic-procedures-performed-by-a-single-surgical-team
#18
Simona Manciu, Mihnea Dragomir, Fabiana Curea, Catalin Vasilescu
BACKGROUND: Despite the obvious technical advantages, the value of robotic surgery is highly debated and its cost-effectiveness has been questioned. The aim of this article is to provide an evaluation of the outcomes of robotic surgery in comparison to conventional laparoscopy. METHODS: A decision analysis based on the Bayes' theorem and the decision tree was used. The robotic approach was compared with the laparoscopic approach for each of the pathologies discussed in this study...
February 22, 2017: Journal of Laparoendoscopic & Advanced Surgical Techniques. Part A
https://www.readbyqxmd.com/read/28224498/differential-gene-expression-dex-and-alternative-splicing-events-ase-for-temporal-dynamic-processes-using-hmms-and-hierarchical-bayesian-modeling-approaches
#19
Sunghee Oh, Seongho Song
In gene expression profile, data analysis pipeline is categorized into four levels, major downstream tasks, i.e., (1) identification of differential expression; (2) clustering co-expression patterns; (3) classification of subtypes of samples; and (4) detection of genetic regulatory networks, are performed posterior to preprocessing procedure such as normalization techniques. To be more specific, temporal dynamic gene expression data has its inherent feature, namely, two neighboring time points (previous and current state) are highly correlated with each other, compared to static expression data which samples are assumed as independent individuals...
2017: Methods in Molecular Biology
https://www.readbyqxmd.com/read/28224368/generalized-fiducial-inference-for-logistic-graded-response-models
#20
Yang Liu, Jan Hannig
Samejima's graded response model (GRM) has gained popularity in the analyses of ordinal response data in psychological, educational, and health-related assessment. Obtaining high-quality point and interval estimates for GRM parameters attracts a great deal of attention in the literature. In the current work, we derive generalized fiducial inference (GFI) for a family of multidimensional graded response model, implement a Gibbs sampler to perform fiducial estimation, and compare its finite-sample performance with several commonly used likelihood-based and Bayesian approaches via three simulation studies...
February 21, 2017: Psychometrika
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