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Big Data

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https://www.readbyqxmd.com/read/27642721/review-of-the-new-abcs-of-research-achieving-breakthrough-collaborations
#1
Vasant Dhar
No abstract text is available yet for this article.
September 2016: Big Data
https://www.readbyqxmd.com/read/27642720/unsupervised-tensor-mining-for-big-data-practitioners
#2
Evangelos E Papalexakis, Christos Faloutsos
Multiaspect data are ubiquitous in modern Big Data applications. For instance, different aspects of a social network are the different types of communication between people, the time stamp of each interaction, and the location associated to each individual. How can we jointly model all those aspects and leverage the additional information that they introduce to our analysis? Tensors, which are multidimensional extensions of matrices, are a principled and mathematically sound way of modeling such multiaspect data...
September 2016: Big Data
https://www.readbyqxmd.com/read/27642719/a-moment-matching-approach-for-generating-synthetic-data
#3
Brittany Megan Bogle, Sanjay Mehrotra
Synthetic data are becoming increasingly important mechanisms for sharing data among collaborators and with the public. Multiple methods for the generation of synthetic data have been proposed, but many have short comings with respect to maintaining the statistical properties of the original data. We propose a new method for fully synthetic data generation that leverages linear and integer mathematical programming models in order to match the moments of the original data in the synthetic data. This method has no inherent disclosure risk and does not require parametric or distributional assumptions...
September 2016: Big Data
https://www.readbyqxmd.com/read/27642718/from-value-assessment-to-value-cocreation-informing-clinical-decision-making-with-medical-claims-data
#4
Steven Thompson, Stephen Varvel, Maciek Sasinowski, James P Burke
Big data and advances in analytical processes represent an opportunity for the healthcare industry to make better evidence-based decisions on the value generated by various tests, procedures, and interventions. Value-based reimbursement is the process of identifying and compensating healthcare providers based on whether their services improve quality of care without increasing cost of care or maintain quality of care while decreasing costs. In this article, we motivate and illustrate the potential opportunities for payers and providers to collaborate and evaluate the clinical and economic efficacy of different healthcare services...
September 2016: Big Data
https://www.readbyqxmd.com/read/27642717/big-data-as-an-enabler-of-primary-education
#5
Vasant Dhar, Nandan Nilekani, Shankar Maruwada, Nagaraju Pappu
No abstract text is available yet for this article.
September 2016: Big Data
https://www.readbyqxmd.com/read/27541627/identifying-and-investigating-unexpected-response-to-treatment-a-diabetes-case-study
#6
Michal Ozery-Flato, Liat Ein-Dor, Naama Parush-Shear-Yashuv, Ranit Aharonov, Hani Neuvirth, Martin S Kohn, Jianying Hu
The availability of electronic health records creates fertile ground for developing computational models of various medical conditions. We present a new approach for detecting and analyzing patients with unexpected responses to treatment, building on machine learning and statistical methodology. Given a specific patient, we compute a statistical score for the deviation of the patient's response from responses observed in other patients having similar characteristics and medication regimens. These scores are used to define cohorts of patients showing deviant responses...
September 2016: Big Data
https://www.readbyqxmd.com/read/27441718/correction-to-big-data-2016-4-60-66
#7
(no author information available yet)
No abstract text is available yet for this article.
June 2016: Big Data
https://www.readbyqxmd.com/read/27441717/improving-the-efficiency-and-ease-of-healthcare-analysis-through-use-of-data-visualization-dashboards
#8
Jennifer G Stadler, Kipp Donlon, Jordan D Siewert, Tessa Franken, Nathaniel E Lewis
The digitization of a patient's health record has profoundly impacted medicine and healthcare. The compilation and accessibility of medical history has provided clinicians an unprecedented, holistic account of a patient's conditions, procedures, medications, family history, and social situation. In addition to the bedside benefits, this level of information has opened the door for population-level monitoring and research, the results of which can be used to guide initiatives that are aimed at improving quality of care...
June 2016: Big Data
https://www.readbyqxmd.com/read/27441716/an-exercise-in-exploring-big-data-for-producing-reliable-statistical-information
#9
Pilar Rey-Del-Castillo, Jesús Cardeñosa
The availability of copious data about many human, social, and economic phenomena is considered an opportunity for the production of official statistics. National statistical organizations and other institutions are more and more involved in new projects for developing what is sometimes seen as a possible change of paradigm in the way statistical figures are produced. Nevertheless, there are hardly any systems in production using Big Data sources. Arguments of confidentiality, data ownership, representativeness, and others make it a difficult task to get results in the short term...
June 2016: Big Data
https://www.readbyqxmd.com/read/27441715/visualizing-dynamic-bitcoin-transaction-patterns
#10
Dan McGinn, David Birch, David Akroyd, Miguel Molina-Solana, Yike Guo, William J Knottenbelt
This work presents a systemic top-down visualization of Bitcoin transaction activity to explore dynamically generated patterns of algorithmic behavior. Bitcoin dominates the cryptocurrency markets and presents researchers with a rich source of real-time transactional data. The pseudonymous yet public nature of the data presents opportunities for the discovery of human and algorithmic behavioral patterns of interest to many parties such as financial regulators, protocol designers, and security analysts. However, retaining visual fidelity to the underlying data to retain a fuller understanding of activity within the network remains challenging, particularly in real time...
June 2016: Big Data
https://www.readbyqxmd.com/read/27441714/integration-and-visualization-of-translational-medicine-data-for-better-understanding-of-human-diseases
#11
Venkata Satagopam, Wei Gu, Serge Eifes, Piotr Gawron, Marek Ostaszewski, Stephan Gebel, Adriano Barbosa-Silva, Rudi Balling, Reinhard Schneider
Translational medicine is a domain turning results of basic life science research into new tools and methods in a clinical environment, for example, as new diagnostics or therapies. Nowadays, the process of translation is supported by large amounts of heterogeneous data ranging from medical data to a whole range of -omics data. It is not only a great opportunity but also a great challenge, as translational medicine big data is difficult to integrate and analyze, and requires the involvement of biomedical experts for the data processing...
June 2016: Big Data
https://www.readbyqxmd.com/read/27441713/visual-circular-analysis-of-266-years-of-sunspot-counts
#12
Bart Buelens
Sunspots, colder areas that are visible as dark spots on the surface of the Sun, have been observed for centuries. Their number varies with a period of ∼11 years, a phenomenon closely related to the solar activity cycle. Recently, observation records dating back to 1749 have been reassessed, resulting in the release of a time series of sunspot numbers covering 266 years of observations. This series is analyzed using circular analysis to determine the periodicity of the occurrence of solar maxima. The circular analysis is combined with spiral graphs to provide a single visualization, simultaneously showing the periodicity of the series, the degree to which individual cycle lengths deviate from the average period, and differences in levels reached during the different maxima...
June 2016: Big Data
https://www.readbyqxmd.com/read/27441712/a-framework-for-considering-comprehensibility-in-modeling
#13
Michael Gleicher
Comprehensibility in modeling is the ability of stakeholders to understand relevant aspects of the modeling process. In this article, we provide a framework to help guide exploration of the space of comprehensibility challenges. We consider facets organized around key questions: Who is comprehending? Why are they trying to comprehend? Where in the process are they trying to comprehend? How can we help them comprehend? How do we measure their comprehension? With each facet we consider the broad range of options...
June 2016: Big Data
https://www.readbyqxmd.com/read/27441711/visualization-for-data-science-adding-credibility-legitimacy-and-saliency
#14
Ross Maciejewski, Douglas C Montgomery
No abstract text is available yet for this article.
June 2016: Big Data
https://www.readbyqxmd.com/read/27441710/call-for-papers-special-issue-on-social-and-technical-trade-offs
#15
Solon Barocas, Danah Boyd, Sorelle Friedler, Hanna Wallach
No abstract text is available yet for this article.
June 2016: Big Data
https://www.readbyqxmd.com/read/27441709/call-for-papers-special-issue-on-big-data-in-robotics
#16
Jeannette Bohg, Matei Ciocarlie, Javier Civera, Lydia E Kavraki
No abstract text is available yet for this article.
June 2016: Big Data
https://www.readbyqxmd.com/read/27441586/acknowledgment-of-reviewers-2015
#17
(no author information available yet)
No abstract text is available yet for this article.
March 2016: Big Data
https://www.readbyqxmd.com/read/27441585/a-case-study-analyzing-city-vitality-with-four-pillars-of-activity-live-work-shop-and-play
#18
Matt Griffin, Blake W Nordstrom, Jon Scholes, Kate Joncas, Patrick Gordon, Elliott Krivenko, Winston Haynes, Roger Higdon, Elizabeth Stewart, Natali Kolker, Elizabeth Montague, Eugene Kolker
This case study evaluates and tracks vitality of a city (Seattle), based on a data-driven approach, using strategic, robust, and sustainable metrics. This case study was collaboratively conducted by the Downtown Seattle Association (DSA) and CDO Analytics teams. The DSA is a nonprofit organization focused on making the city of Seattle and its Downtown a healthy and vibrant place to Live, Work, Shop, and Play. DSA primarily operates through public policy advocacy, community and business development, and marketing...
March 2016: Big Data
https://www.readbyqxmd.com/read/27441584/combining-human-computing-and-machine-learning-to-make-sense-of-big-aerial-data-for-disaster-response
#19
Ferda Ofli, Patrick Meier, Muhammad Imran, Carlos Castillo, Devis Tuia, Nicolas Rey, Julien Briant, Pauline Millet, Friedrich Reinhard, Matthew Parkan, Stéphane Joost
Aerial imagery captured via unmanned aerial vehicles (UAVs) is playing an increasingly important role in disaster response. Unlike satellite imagery, aerial imagery can be captured and processed within hours rather than days. In addition, the spatial resolution of aerial imagery is an order of magnitude higher than the imagery produced by the most sophisticated commercial satellites today. Both the United States Federal Emergency Management Agency (FEMA) and the European Commission's Joint Research Center (JRC) have noted that aerial imagery will inevitably present a big data challenge...
March 2016: Big Data
https://www.readbyqxmd.com/read/27441583/patient-experience-of-australian-general-practices
#20
Ajit Narayanan, Michael Greco
The number of data-based research articles focusing on patient sociodemographic profiling and experience with healthcare practices is still relatively small. One of the reasons for this relative lack of research is that categorizing patients into different demographic groups can lead to significant reductions in sample numbers for homogeneous subgroups. The aim of this article is to identify problems and issues when dealing with big data that contains information at two levels: patient experience of their general practice, and scores received by practices...
March 2016: Big Data
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