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https://www.readbyqxmd.com/read/28926310/coronary-ct-angiography-derived-fractional-flow-reserve
#1
Christian Tesche, Carlo N De Cecco, Moritz H Albrecht, Taylor M Duguay, Richard R Bayer, Sheldon E Litwin, Daniel H Steinberg, U Joseph Schoepf
Invasive coronary angiography (ICA) with measurement of fractional flow reserve (FFR) by means of a pressure wire technique is the established reference standard for the functional assessment of coronary artery disease (CAD) ( 1 , 2 ). Coronary computed tomographic (CT) angiography has emerged as a noninvasive method for direct assessment of CAD and plaque characterization with high diagnostic accuracy compared with ICA ( 3 , 4 ). However, the solely anatomic assessment provided with both coronary CT angiography and ICA has poor discriminatory power for ischemia-inducing lesions...
October 2017: Radiology
https://www.readbyqxmd.com/read/28922353/synthesizing-developmental-trajectories
#2
Paul Villoutreix, Joakim Andén, Bomyi Lim, Hang Lu, Ioannis G Kevrekidis, Amit Singer, Stanislav Y Shvartsman
Dynamical processes in biology are studied using an ever-increasing number of techniques, each of which brings out unique features of the system. One of the current challenges is to develop systematic approaches for fusing heterogeneous datasets into an integrated view of multivariable dynamics. We demonstrate that heterogeneous data fusion can be successfully implemented within a semi-supervised learning framework that exploits the intrinsic geometry of high-dimensional datasets. We illustrate our approach using a dataset from studies of pattern formation in Drosophila...
September 18, 2017: PLoS Computational Biology
https://www.readbyqxmd.com/read/28922296/trajectories-of-glycemic-change-in-a-national-cohort-of-adults-with-previously-controlled-type-2-diabetes
#3
Rozalina G McCoy, Che Ngufor, Holly K Van Houten, Brian Caffo, Nilay D Shah
BACKGROUND: Individualized diabetes management would benefit from prospectively identifying well-controlled patients at risk of losing glycemic control. OBJECTIVES: To identify patterns of hemoglobin A1c (HbA1c) change among patients with stable controlled diabetes. RESEARCH DESIGN: Cohort study using OptumLabs Data Warehouse, 2001-2013. We develop and apply a machine learning framework that uses a Bayesian estimation of the mixture of generalized linear mixed effect models to discover glycemic trajectories, and a random forest feature contribution method to identify patient characteristics predictive of their future glycemic trajectories...
September 15, 2017: Medical Care
https://www.readbyqxmd.com/read/28922127/jointly-learning-structured-analysis-discriminative-dictionary-and-analysis-multiclass-classifier
#4
Zhao Zhang, Weiming Jiang, Jie Qin, Li Zhang, Fanzhang Li, Min Zhang, Shuicheng Yan
In this paper, we propose an analysis mechanism-based structured analysis discriminative dictionary learning (ADDL) framework. The ADDL seamlessly integrates ADDL, analysis representation, and analysis classifier training into a unified model. The applied analysis mechanism can make sure that the learned dictionaries, representations, and linear classifiers over different classes are independent and discriminating as much as possible. The dictionary is obtained by minimizing a reconstruction error and an analytical incoherence promoting term that encourages the subdictionaries associated with different classes to be independent...
September 14, 2017: IEEE Transactions on Neural Networks and Learning Systems
https://www.readbyqxmd.com/read/28918390/a-glossary-for-big-data-in-population-and-public-health-discussion-and-commentary-on-terminology-and-research-methods
#5
Daniel Fuller, Richard Buote, Kevin Stanley
The volume and velocity of data are growing rapidly and big data analytics are being applied to these data in many fields. Population and public health researchers may be unfamiliar with the terminology and statistical methods used in big data. This creates a barrier to the application of big data analytics. The purpose of this glossary is to define terms used in big data and big data analytics and to contextualise these terms. We define the five Vs of big data and provide definitions and distinctions for data mining, machine learning and deep learning, among other terms...
September 16, 2017: Journal of Epidemiology and Community Health
https://www.readbyqxmd.com/read/28912801/efficient-multiple-kernel-learning-algorithms-using-low-rank-representation
#6
Wenjia Niu, Kewen Xia, Baokai Zu, Jianchuan Bai
Unlike Support Vector Machine (SVM), Multiple Kernel Learning (MKL) allows datasets to be free to choose the useful kernels based on their distribution characteristics rather than a precise one. It has been shown in the literature that MKL holds superior recognition accuracy compared with SVM, however, at the expense of time consuming computations. This creates analytical and computational difficulties in solving MKL algorithms. To overcome this issue, we first develop a novel kernel approximation approach for MKL and then propose an efficient Low-Rank MKL (LR-MKL) algorithm by using the Low-Rank Representation (LRR)...
2017: Computational Intelligence and Neuroscience
https://www.readbyqxmd.com/read/28902323/hand-hygiene-compliance-of-healthcare-professionals-in-an-emergency-department
#7
Caroline Zottele, Tania Solange Bosi de Souza Magnago, Angela Isabel Dos Santos Dullius, Adriane Cristina Bernat Kolankiewicz, Juliana Dal Ongaro
OBJECTIVE: To analyze compliance with hand hygiene by healthcare professionals in an emergency department unit. METHOD: This is a longitudinal quantitative study developed in 2015 with healthcare professionals from a university hospital in the state of Rio Grande do Sul. Each professional was monitored three times by direct non-participant observation at WHO's five recommended moments in hand hygiene, taking the concepts of opportunity, indication and action into account...
August 28, 2017: Revista da Escola de Enfermagem da U S P
https://www.readbyqxmd.com/read/28899843/a-machine-learning-approach-for-the-identification-of-new-biomarkers-for-knee-osteoarthritis-development-in-overweight-and-obese-women
#8
N Lazzarini, J Runhaar, A C Bay-Jensen, C S Thudium, S M A Bierma-Zeinstra, Y Henrotin, J Bacardit
OBJECTIVE: Knee osteoarthritis (OA) is among the higher contributors to global disability. Despite its high prevalence, currently, there is no cure for this disease. Furthermore, the available diagnostic approaches have large precision errors and low sensitivity. Therefore, there is a need for new biomarkers to correctly identify early knee OA. METHOD: We have created an analytics pipeline based on machine learning to identify small models (having few variables) that predict the 30-months incidence of knee OA (using multiple clinical and structural OA outcome measures) in overweight middle-aged women without knee OA at baseline...
September 9, 2017: Osteoarthritis and Cartilage
https://www.readbyqxmd.com/read/28888332/machine-learning-based-electronic-triage-more-accurately-differentiates-patients-with-respect-to%C3%A2-clinical-outcomes-compared-with-the-emergency-severity-index
#9
Scott Levin, Matthew Toerper, Eric Hamrock, Jeremiah S Hinson, Sean Barnes, Heather Gardner, Andrea Dugas, Bob Linton, Tom Kirsch, Gabor Kelen
STUDY OBJECTIVE: Standards for emergency department (ED) triage in the United States rely heavily on subjective assessment and are limited in their ability to risk-stratify patients. This study seeks to evaluate an electronic triage system (e-triage) based on machine learning that predicts likelihood of acute outcomes enabling improved patient differentiation. METHODS: A multisite, retrospective, cross-sectional study of 172,726 ED visits from urban and community EDs was conducted...
September 6, 2017: Annals of Emergency Medicine
https://www.readbyqxmd.com/read/28888192/what-counts-in-preschool-number-knowledge-a-bayes-factor-analytic-approach-toward-theoretical-model-development
#10
Yi Mou, Ilaria Berteletti, Daniel C Hyde
Preschool children vary tremendously in their numerical knowledge, and these individual differences strongly predict later mathematics achievement. To better understand the sources of these individual differences, we measured a variety of cognitive and linguistic abilities motivated by previous literature to be important and then analyzed which combination of these variables best explained individual differences in actual number knowledge. Through various data-driven Bayesian model comparison and selection strategies on competing multiple regression models, our analyses identified five variables of unique importance to explaining individual differences in preschool children's symbolic number knowledge: knowledge of the count list, nonverbal approximate numerical ability, working memory, executive conflict processing, and knowledge of letters and words...
September 6, 2017: Journal of Experimental Child Psychology
https://www.readbyqxmd.com/read/28887351/using-predictive-analytics-and-big-data-to-optimize-pharmaceutical-outcomes
#11
Inmaculada Hernandez, Yuting Zhang
PURPOSE: The steps involved, the resources needed, and the challenges associated with applying predictive analytics in healthcare are described, with a review of successful applications of predictive analytics in implementing population health management interventions that target medication-related patient outcomes. SUMMARY: In healthcare, the term big data typically refers to large quantities of electronic health record, administrative claims, and clinical trial data as well as data collected from smartphone applications, wearable devices, social media, and personal genomics services; predictive analytics refers to innovative methods of analysis developed to overcome challenges associated with big data, including a variety of statistical techniques ranging from predictive modeling to machine learning to data mining...
September 15, 2017: American Journal of Health-system Pharmacy: AJHP
https://www.readbyqxmd.com/read/28886410/a-methodology-to-design-heuristics-for-model-selection-based-on-the-characteristics-of-data-application-to-investigate-when-the-negative-binomial-lindley-nb-l-is-preferred-over-the-negative-binomial-nb
#12
Mohammadali Shirazi, Soma Sekhar Dhavala, Dominique Lord, Srinivas Reddy Geedipally
Safety analysts usually use post-modeling methods, such as the Goodness-of-Fit statistics or the Likelihood Ratio Test, to decide between two or more competitive distributions or models. Such metrics require all competitive distributions to be fitted to the data before any comparisons can be accomplished. Given the continuous growth in introducing new statistical distributions, choosing the best one using such post-modeling methods is not a trivial task, in addition to all theoretical or numerical issues the analyst may face during the analysis...
September 5, 2017: Accident; Analysis and Prevention
https://www.readbyqxmd.com/read/28885167/event-triggered-distributed-control-of-nonlinear-interconnected-systems-using-online-reinforcement-learning-with-exploration
#13
Vignesh Narayanan, Sarangapani Jagannathan
In this paper, a distributed control scheme for an interconnected system composed of uncertain input affine nonlinear subsystems with event triggered state feedback is presented by using a novel hybrid learning scheme-based approximate dynamic programming with online exploration. First, an approximate solution to the Hamilton-Jacobi-Bellman equation is generated with event sampled neural network (NN) approximation and subsequently, a near optimal control policy for each subsystem is derived. Artificial NNs are utilized as function approximators to develop a suite of identifiers and learn the dynamics of each subsystem...
September 7, 2017: IEEE Transactions on Cybernetics
https://www.readbyqxmd.com/read/28881977/denoising-genome-wide-histone-chip-seq-with-convolutional-neural-networks
#14
Pang Wei Koh, Emma Pierson, Anshul Kundaje
Motivation: Chromatin immune-precipitation sequencing (ChIP-seq) experiments are commonly used to obtain genome-wide profiles of histone modifications associated with different types of functional genomic elements. However, the quality of histone ChIP-seq data is affected by many experimental parameters such as the amount of input DNA, antibody specificity, ChIP enrichment and sequencing depth. Making accurate inferences from chromatin profiling experiments that involve diverse experimental parameters is challenging...
July 15, 2017: Bioinformatics
https://www.readbyqxmd.com/read/28880195/lann-svd-a-non-iterative-svd-based-learning-algorithm-for-one-layer-neural-networks
#15
Oscar Fontenla-Romero, Beatriz Perez-Sanchez, Bertha Guijarro-Berdinas
In the scope of data analytics, the volume of a data set can be defined as a product of instance size and dimensionality of the data. In many real problems, data sets are mainly large only on one of these aspects. Machine learning methods proposed in the literature are able to efficiently learn in only one of these two situations, when the number of variables is much greater than instances or vice versa. However, there is no proposal allowing to efficiently handle either circumstances in a large-scale scenario...
September 1, 2017: IEEE Transactions on Neural Networks and Learning Systems
https://www.readbyqxmd.com/read/28879861/integrating-exhaled-breath-diagnostics-by-disease-sniffing-dogs-with-instrumental-laboratory-analysis
#16
Joachim Pleil, Roger Giese
Dogs have been studied for many years as a medical diagnostic tool to detect a pre-clinical disease state by sniffing emissions directly from a human or an in vitro biological sample. Some of the studies report high sensitivity and specificity in blinded case-control studies. However, in these studies it is completely unknown as to which suites of chemicals the dogs detect and how they ultimately interpret this information amidst confounding background odors. Herein, we consider the advantages and challenges of canine olfaction for early (meaningful) detection of cancer, and propose an experimental concept to narrow the molecular signals used by the dog for sample classification to laboratory-based instrumental analysis...
September 7, 2017: Journal of Breath Research
https://www.readbyqxmd.com/read/28876692/paediatric-splenectomy-the-johannesburg-experience
#17
N Patel, A Nicola, P Bennett, E Mapunda, J Loveland, A Grieve
BACKGROUND: Splenectomy is uncommon in children and data on splenectomies in the South African paediatric population is sparse. A deeper understanding of the demographics, indications, techniques, and postoperative management of patients requiring splenectomy may improve care. METHOD: Patient records for all splenectomies performed in children aged 0 to 16 years at Charlotte Maxeke Johannesburg Academic (CMJAH) and Chris Hani Baragwanath Academic Hospitals (CHBAH) between 2000 and 2015 were reviewed...
June 2017: South African Journal of Surgery. Suid-Afrikaanse Tydskrif Vir Chirurgie
https://www.readbyqxmd.com/read/28876450/what-has-become-of-critique-reassembling-sociology-after-latour
#18
Tom Mills
This paper offers a defence of sociology through an engagement with Actor Network Theory (ANT) and particularly the critique of 'critical' and politically engaged social science developed by Bruno Latour. It argues that ANT identifies some weaknesses in more conventional sociology and social theory, and suggests that 'critical' and 'public' orientated sociologists can learn from the analytical precision and ethnographic sensibilities that characterize ANT as a framework of analysis and a research programme...
September 6, 2017: British Journal of Sociology
https://www.readbyqxmd.com/read/28871622/-heartfailurematters-org-an-educational-website-for-patients-and-carers-from-the-heart-failure-association-of-the-european-society-of-cardiology-objectives-use-and-future-directions
#19
Kim P Wagenaar, Frans H Rutten, Leonie Klompstra, Yusuf Bhana, Floor Sieverink, Frank Ruschitzka, Petar M Seferovic, Mitja Lainscak, Massimo F Piepoli, Berna D L Broekhuizen, Anna Strömberg, Tiny Jaarsma, Arno W Hoes, Kenneth Dickstein
AIMS: In 2007, the Heart Failure Association of the European Society of Cardiology (ESC) launched the information website heartfailurematters.org (HFM site) with the aim of creating a practical tool through which to provide advice and guidelines for living with heart failure to patients, their carers, health care professionals and the general public worldwide. The website is managed by the ESC at the European Heart House and is currently available in nine languages. The aim of this study is to describe the background, objectives, use, lessons learned and future directions of the HFM site...
September 4, 2017: European Journal of Heart Failure
https://www.readbyqxmd.com/read/28871252/development-and-characterization-of-a-camelid-single-domain-antibody-urease-conjugate-that-targets-vascular-endothelial-growth-factor-receptor-2
#20
Baomin Tian, Wah Yau Wong, Marni D Uger, Pawel Wisniewski, Heman Chao
Angiogenesis is the process of new blood vessel formation and is essential for a tumor to grow beyond a certain size. Tumors secrete the pro-angiogenic factor vascular endothelial growth factor, which acts upon local endothelial cells by binding to vascular endothelial growth factor receptors (VEGFRs). In this study, we describe the development and characterization of V21-DOS47, an immunoconjugate that targets VEGFR2. V21-DOS47 is composed of a camelid single domain anti-VEGFR2 antibody (V21) and the enzyme urease...
2017: Frontiers in Immunology
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