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https://www.readbyqxmd.com/read/27918664/modern-techniques-and-technologies-applied-to-training-and-performance-monitoring
#1
William A Sands, Ashley A Kavanaugh, Steven R Murray, Jeni R McNeal, Monèm Jemni
Athlete preparation and performance continues to increase in complexity and costs. Modern coaches are shifting from reliance on personal memory, experience, and opinion to evidence from collected training load data. Training load monitoring may hold vital information for developing systems of monitoring that follow the training process with such precision that both performance prediction and day-to-day management of training become an adjunct to preparation and performance. Time series data collection and analyses in sport are still in their infancy with considerable efforts being applied in "big-data" analytics and models of the appropriate variables to monitor and methods for doing so...
December 5, 2016: International Journal of Sports Physiology and Performance
https://www.readbyqxmd.com/read/27918178/a-practical-guide-to-big-data-research-in-psychology
#2
Eric Evan Chen, Sean P Wojcik
The massive volume of data that now covers a wide variety of human behaviors offers researchers in psychology an unprecedented opportunity to conduct innovative theory- and data-driven field research. This article is a practical guide to conducting big data research, covering data management, acquisition, processing, and analytics (including key supervised and unsupervised learning data mining methods). It is accompanied by walkthrough tutorials on data acquisition, text analysis with latent Dirichlet allocation topic modeling, and classification with support vector machines...
December 2016: Psychological Methods
https://www.readbyqxmd.com/read/27873357/use-of-big-data-for-drug-development-and-for-public-and-personal-health-and-care
#3
Lada Leyens, Matthias Reumann, Nuria Malats, Angela Brand
The use of data analytics across the entire healthcare value chain, from drug discovery and development through epidemiology to informed clinical decision for patients or policy making for public health, has seen an explosion in the recent years. The increase in quantity and variety of data available together with the improvement of storing capabilities and analytical tools offer numerous possibilities to all stakeholders (manufacturers, regulators, payers, healthcare providers, decision makers, researchers) but most importantly, it has the potential to improve general health outcomes if we learn how to exploit it in the right way...
November 21, 2016: Genetic Epidemiology
https://www.readbyqxmd.com/read/27872036/challenges-and-opportunities-of-big-data-in-health-care-a-systematic-review
#4
REVIEW
Clemens Scott Kruse, Rishi Goswamy, Yesha Raval, Sarah Marawi
BACKGROUND: Big data analytics offers promise in many business sectors, and health care is looking at big data to provide answers to many age-related issues, particularly dementia and chronic disease management. OBJECTIVE: The purpose of this review was to summarize the challenges faced by big data analytics and the opportunities that big data opens in health care. METHODS: A total of 3 searches were performed for publications between January 1, 2010 and January 1, 2016 (PubMed/MEDLINE, CINAHL, and Google Scholar), and an assessment was made on content germane to big data in health care...
November 21, 2016: JMIR Medical Informatics
https://www.readbyqxmd.com/read/27862002/distributed-data-networks-a-blueprint-for-big-data-sharing-and-healthcare-analytics
#5
Jennifer R Popovic
This paper defines the attributes of distributed data networks and outlines the data and analytic infrastructure needed to build and maintain a successful network. We use examples from one successful implementation of a large-scale, multisite, healthcare-related distributed data network, the U.S. Food and Drug Administration-sponsored Sentinel Initiative. Analytic infrastructure-development concepts are discussed from the perspective of promoting six pillars of analytic infrastructure: consistency, reusability, flexibility, scalability, transparency, and reproducibility...
November 18, 2016: Annals of the New York Academy of Sciences
https://www.readbyqxmd.com/read/27848978/the-impact-of-heterogeneity-and-awareness-in-modeling-epidemic-spreading-on-multiplex-networks
#6
Marialisa Scatà, Alessandro Di Stefano, Pietro Liò, Aurelio La Corte
In the real world, dynamic processes involving human beings are not disjoint. To capture the real complexity of such dynamics, we propose a novel model of the coevolution of epidemic and awareness spreading processes on a multiplex network, also introducing a preventive isolation strategy. Our aim is to evaluate and quantify the joint impact of heterogeneity and awareness, under different socioeconomic conditions. Considering, as case study, an emerging public health threat, Zika virus, we introduce a data-driven analysis by exploiting multiple sources and different types of data, ranging from Big Five personality traits to Google Trends, related to different world countries where there is an ongoing epidemic outbreak...
November 16, 2016: Scientific Reports
https://www.readbyqxmd.com/read/27830253/clinical-research-informatics-for-big-data-and-precision-medicine
#7
C Weng, M G Kahn
OBJECTIVES: To reflect on the notable events and significant developments in Clinical Research Informatics (CRI) in the year of 2015 and discuss near-term trends impacting CRI. METHODS: We selected key publications that highlight not only important recent advances in CRI but also notable events likely to have significant impact on CRI activities over the next few years or longer, and consulted the discussions in relevant scientific communities and an online living textbook for modern clinical trials...
November 10, 2016: Yearbook of Medical Informatics
https://www.readbyqxmd.com/read/27827859/precision-health-economics-and-outcomes-research-to-support-precision-medicine-big-data-meets-patient-heterogeneity-on-the-road-to-value
#8
Yixi Chen, Gregory F Guzauskas, Chengming Gu, Bruce C M Wang, Wesley E Furnback, Guotong Xie, Peng Dong, Louis P Garrison
The "big data" era represents an exciting opportunity to utilize powerful new sources of information to reduce clinical and health economic uncertainty on an individual patient level. In turn, health economic outcomes research (HEOR) practices will need to evolve to accommodate individual patient-level HEOR analyses. We propose the concept of "precision HEOR", which utilizes a combination of costs and outcomes derived from big data to inform healthcare decision-making that is tailored to highly specific patient clusters or individuals...
November 2, 2016: Journal of Personalized Medicine
https://www.readbyqxmd.com/read/27819294/big-genomics-and-clinical-data-analytics-strategies-for-precision-cancer-prognosis
#9
Ghim Siong Ow, Vladimir A Kuznetsov
The field of personalized and precise medicine in the era of big data analytics is growing rapidly. Previously, we proposed our model of patient classification termed Prognostic Signature Vector Matching (PSVM) and identified a 37 variable signature comprising 36 let-7b associated prognostic significant mRNAs and the age risk factor that stratified large high-grade serous ovarian cancer patient cohorts into three survival-significant risk groups. Here, we investigated the predictive performance of PSVM via optimization of the prognostic variable weights, which represent the relative importance of one prognostic variable over the others...
November 7, 2016: Scientific Reports
https://www.readbyqxmd.com/read/27814027/harnessing-big-data-for-systems-pharmacology
#10
Lei Xie, Eli J Draizen, Philip E Bourne
Systems pharmacology aims to holistically understand mechanisms of drug actions to support drug discovery and clinical practice. Systems pharmacology modeling (SPM) is data driven. It integrates an exponentially growing amount of data at multiple scales (genetic, molecular, cellular, organismal, and environmental). The goal of SPM is to develop mechanistic or predictive multiscale models that are interpretable and actionable. The current explosions in genomics and other omics data, as well as the tremendous advances in big data technologies, have already enabled biologists to generate novel hypotheses and gain new knowledge through computational models of genome-wide, heterogeneous, and dynamic data sets...
October 13, 2016: Annual Review of Pharmacology and Toxicology
https://www.readbyqxmd.com/read/27812121/inferring-passenger-denial-behavior-of-taxi-drivers-from-large-scale-taxi-traces
#11
Sihai Zhang, Zhiyang Wang
How to understand individual human actions is a fundamental question to modern science, which drives and incurs many social, technological, racial, religious and economic phenomena. Human dynamics tries to reveal the temporal pattern and internal mechanism of human actions in letter or electronic communications, from the perspective of continuous interactions among friends or acquaintances. For interactions between stranger to stranger, taxi industry provide fruitful phenomina and evidence to investigate the action decisions...
2016: PloS One
https://www.readbyqxmd.com/read/27810012/power-to-the-people-addressing-big-data-challenges-in-neuroscience-by-creating-a-new-cadre-of-citizen-neuroscientists
#12
Jane Roskams, Zoran Popović
Global neuroscience projects are producing big data at an unprecedented rate that informatic and artificial intelligence (AI) analytics simply cannot handle. Online games, like Foldit, Eterna, and Eyewire-and now a new neuroscience game, Mozak-are fueling a people-powered research science (PPRS) revolution, creating a global community of "new experts" that over time synergize with computational efforts to accelerate scientific progress, empowering us to use our collective cerebral talents to drive our understanding of our brain...
November 2, 2016: Neuron
https://www.readbyqxmd.com/read/27804279/big-data-predictive-analytics-and-quality-improvement-in-kidney-transplantation-a-proof-of-concept
#13
Titte R Srinivas, David J Taber, Zemin Su, Jingwen Zhang, Girish Mour, David Northrup, Arun Tripathi, Justin E Marsden, William P Moran, Patrick D Mauldin
This article was posted online prematurely. It will be made available again at a later date.
November 2, 2016: American Journal of Transplantation
https://www.readbyqxmd.com/read/27783645/spatial-and-social-media-data-analytics-of-housing-prices-in-shenzhen-china
#14
Chao Wu, Xinyue Ye, Fu Ren, You Wan, Pengfei Ning, Qingyun Du
Housing is among the most pressing issues in urban China and has received considerable scholarly attention. Researchers have primarily concentrated on identifying the factors that influence residential property prices and how such mechanisms function. However, few studies have examined the potential factors that influence housing prices from a big data perspective. In this article, we use a big data perspective to determine the willingness of buyers to pay for various factors. The opinions and geographical preferences of individuals for places can be represented by visit frequencies given different motivations...
2016: PloS One
https://www.readbyqxmd.com/read/27779626/snp-based-heritability-estimates-of-the-personality-dimensions-and-polygenic-prediction-of-both-neuroticism-and-major-depression-findings-from-converge
#15
A R Docherty, A Moscati, R Peterson, A C Edwards, D E Adkins, S A Bacanu, T B Bigdeli, B T Webb, J Flint, K S Kendler
Biometrical genetic studies suggest that the personality dimensions, including neuroticism, are moderately heritable (~0.4 to 0.6). Quantitative analyses that aggregate the effects of many common variants have recently further informed genetic research on European samples. However, there has been limited research to date on non-European populations. This study examined the personality dimensions in a large sample of Han Chinese descent (N=10 064) from the China, Oxford, and VCU Experimental Research on Genetic Epidemiology study, aimed at identifying genetic risk factors for recurrent major depression among a rigorously ascertained cohort...
October 25, 2016: Translational Psychiatry
https://www.readbyqxmd.com/read/27779619/a-database-of-human-exposomes-and-phenomes-from-the-us-national-health-and-nutrition-examination-survey
#16
Chirag J Patel, Nam Pho, Michael McDuffie, Jeremy Easton-Marks, Cartik Kothari, Isaac S Kohane, Paul Avillach
The National Health and Nutrition Examination Survey (NHANES) is a population survey implemented by the Centers for Disease Control and Prevention (CDC) to monitor the health of the United States whose data is publicly available in hundreds of files. This Data Descriptor describes a single unified and universally accessible data file, merging across 255 separate files and stitching data across 4 surveys, encompassing 41,474 individuals and 1,191 variables. The variables consist of phenotype and environmental exposure information on each individual, specifically (1) demographic information, physical exam results (e...
October 25, 2016: Scientific Data
https://www.readbyqxmd.com/read/27765959/machine-learning-and-decision-support-in-critical-care
#17
Alistair E W Johnson, Mohammad M Ghassemi, Shamim Nemati, Katherine E Niehaus, David A Clifton, Gari D Clifford
Clinical data management systems typically provide caregiver teams with useful information, derived from large, sometimes highly heterogeneous, data sources that are often changing dynamically. Over the last decade there has been a significant surge in interest in using these data sources, from simply re-using the standard clinical databases for event prediction or decision support, to including dynamic and patient-specific information into clinical monitoring and prediction problems. However, in most cases, commercial clinical databases have been designed to document clinical activity for reporting, liability and billing reasons, rather than for developing new algorithms...
February 2016: Proceedings of the IEEE
https://www.readbyqxmd.com/read/27756853/novel-analytic-methods-needed-for-real-time-continuous-core-body-temperature-data
#18
Vicki Hertzberg, Valerie Mac, Lisa Elon, Nathan Mutic, Abby Mutic, Katherine Peterman, J Antonio Tovar-Aguilar, Eugenia Economos, Joan Flocks, Linda McCauley
Affordable measurement of core body temperature (Tc) in a continuous, real-time fashion is now possible. With this advance comes a new data analysis paradigm for occupational epidemiology. We characterize issues arising after obtaining Tc data over 188 workdays for 83 participating farmworkers, a population vulnerable to effects of rising temperatures due to climate change. We describe a novel approach to these data using smoothing and functional data analysis. This approach highlights different data aspects compared with describing Tc at a single time point or summaries of the time course into an indicator function (e...
October 18, 2016: Western Journal of Nursing Research
https://www.readbyqxmd.com/read/27754456/an-efficient-recommendation-filter-model-on-smart-home-big-data-analytics-for-enhanced-living-environments
#19
Hao Chen, Xiaoyun Xie, Wanneng Shu, Naixue Xiong
With the rapid growth of wireless sensor applications, the user interfaces and configurations of smart homes have become so complicated and inflexible that users usually have to spend a great amount of time studying them and adapting to their expected operation. In order to improve user experience, a weighted hybrid recommender system based on a Kalman Filter model is proposed to predict what users might want to do next, especially when users are located in a smart home with an enhanced living environment. Specifically, a weight hybridization method was introduced, which combines contextual collaborative filter and the contextual content-based recommendations...
October 15, 2016: Sensors
https://www.readbyqxmd.com/read/27754282/hw-04-3-global-network-for-her-based-big-data-analysis
#20
Peter Rijnbeek
Massive numbers of electronic health records are currently being collected globally, including structured data in the form of diagnoses, medications, laboratory test results, and unstructured data contained in clinical narratives. This opens unprecedented possibilities for research and ultimately patient care. However, actual use of these databases in a multi-center study is severely hampered by a variety of challenges, e.g., each database has a different database structure and uses different terminology systems...
September 2016: Journal of Hypertension
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