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PubMed Journals Articles About "Implementing Culture Driven Data Analytics Approach Support Tech" RSS

16:38 EDT 16th October 2018 | BioPortfolio

Implementing Culture Driven Data Analytics Approach Support Tech PubMed articles on BioPortfolio. Our PubMed references draw on over 21 million records from the medical literature. Here you can see the latest Implementing Culture Driven Data Analytics Approach Support Tech articles that have been published worldwide.

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Showing "Implementing Culture Driven Data Analytics Approach Support Tech" PubMed Articles 1–25 of 43,000+

Structural biology meets data science: does anything change?

Data science has emerged from the proliferation of digital data, coupled with advances in algorithms, software and hardware (e.g., GPU computing). Innovations in structural biology have been driven by similar factors, spurring us to ask: can these two fields impact one another in deep and hitherto unforeseen ways? We posit that the answer is yes. New biological knowledge lies in the relationships between sequence, structure, function and disease, all of which play out on the stage of evolution, and data sci...


Big Data Analytics in Medicine and Healthcare.

This paper surveys big data with highlighting the big data analytics in medicine and healthcare. Big data characteristics: value, volume, velocity, variety, veracity and variability are described. Big data analytics in medicine and healthcare covers integration and analysis of large amount of complex heterogeneous data such as various - omics data (genomics, epigenomics, transcriptomics, proteomics, metabolomics, interactomics, pharmacogenomics, diseasomics), biomedical data and electronic health records da...

A visual analytics approach for pattern-recognition in patient-generated data.

To develop and test a visual analytics tool to help clinicians identify systematic and clinically meaningful patterns in patient-generated data (PGD) while decreasing perceived information overload.


Special Issue on Profit-Driven Analytics.

Commercial Visual Analytics Systems-Advances in the Big Data Analytics Field.

Five years after the first state-of-the-art report on Commercial Visual Analytics Systems we present a reevaluation of the Big Data Analytics field. We build on the success of the 2012 survey, which was influential even beyond the boundaries of the InfoVis and Visual Analytics (VA) community. While the field has matured significantly since the original survey, we find that innovation and research-driven development are increasingly sacrificed to satisfy a wide range of user groups. We evaluate new product v...

Profit-Based Model Selection for Customer Retention Using Individual Customer Lifetime Values.

The goal of customer retention campaigns, by design, is to add value and enhance the operational efficiency of businesses. For organizations that strive to retain their customers in saturated, and sometimes fast moving, markets such as the telecommunication and banking industries, implementing customer churn prediction models that perform well and in accordance with the business goals is vital. The expected maximum profit (EMP) measure is tailored toward this problem by taking into account the costs and ben...

Spatio-Temporal Urban Data Analysis: A Visual Analytics Perspective.

Visual analytics systems can greatly help in the analysis of urban data allowing domain experts from academia and city governments to better understand cities, and thus enable better operations, informed planning and policies. Effectively designing these systems is challenging and requires bringing together methods from different domains. In this paper, we discuss the challenges involved in designing a visual analytics system to interactively explore large spatio-temporal data sets and give an overview of o...

Inter-subject phase synchronization for exploratory analysis of task-fMRI.

Analysis of task-based fMRI data is conventionally carried out using a hypothesis-driven approach, where blood-oxygen-level dependent (BOLD) time courses are correlated with a hypothesized temporal structure. In some experimental designs, this temporal structure can be difficult to define. In other cases, experimenters may wish to take a more exploratory, data-driven approach to detecting task-driven BOLD activity. In this study, we demonstrate the efficiency and power of an inter-subject synchronization ap...

A crossroads in predictive analytics monitoring for clinical medicine.

A new goal for medical informatics is to develop robust tools that integrate clinical data on a patient in order to estimate the risk of imminent adverse events. This new field of predictive analytics monitoring is growing very quickly. Its claims, however, can be vulnerable when clinicians fail to use the best mathematical and statistical tools, when quantitative scientists fail to grasp the nuances of clinical medicine, and when either fails to incorporate knowledge of physiology. Its potential, though is...

Opening the Black Box: Understanding the Science Behind Big Data and Predictive Analytics.

Big data, smart data, predictive analytics, and other similar terms are ubiquitous in the lay and scientific literature. However, despite the frequency of usage, these terms are often poorly understood, and evidence of their disruption to clinical care is hard to find. This article aims to address these issues by first defining and elucidating the term big data, exploring the ways in which modern medical data, both inside and outside the electronic medical record, meet the established definitions of big dat...

Big-BOE: Fusing Spanish Official Gazette with Big Data Technology.

The proliferation of new data sources, stemmed from the adoption of open-data schemes, in combination with an increasing computing capacity causes the inception of new type of analytics that process Internet of things with low-cost engines to speed up data processing using parallel computing. In this context, the article presents an initiative, called BIG-Boletín Oficial del Estado (BOE), designed to process the Spanish official government gazette (BOE) with state-of-the-art processing engines, to reduce c...

Laparoscopic sacrocolpopexy with or without midurethral sling insertion: Is a two- step approach justified? A prospective study.

Most data support the fact that women with symptomatic pelvic organ prolapse (POP) with concomitant symptomatic or occult stress urinary incontinence (SUI) benefit from concurrent POP and anti-incontinence procedure. However some data support a delayed or 2-step approach. The aim of this study was to demonstrate the effectiveness and safety of laparoscopic sacrocolpopexy (SCP) alone with a delayed approach for SUI to prove the justification of a 2-step approach.

BIG DATA ANALYTICS AND PRECISION ANIMAL AGRICULTURE SYMPOSIUM: Data to decisions.

Big data are frequently used in many facets of business and agronomy to enhance knowledge needed to improve operational decisions. Livestock operations collect data of sufficient quantity to perform predictive analytics. Predictive analytics can be defined as a methodology and suite of data evaluation techniques to generate a prediction for specific target outcomes. The objective of this manuscript is to describe the process of using big data and the predictive analytic framework to create tools to drive de...

Visual Analytics for Topic Model Optimization based on User-Steerable Speculative Execution.

To effectively assess the potential consequences of human interventions in model-driven analytics systems, we establish the concept of speculative execution as a visual analytics paradigm for creating user-steerable preview mechanisms. This paper presents an explainable, mixed-initiative topic modeling framework that integrates speculative execution into the algorithmic decisionmaking process. Our approach visualizes the model-space of our novel incremental hierarchical topic modeling algorithm, unveiling i...

A programmatic approach to address increasing HIV diagnoses among Hispanic/Latino MSM, 2010-2014.

From 2010 to 2015, young (13-24 years) Hispanic/Latino gay, bisexual and other men who have sex with men (MSM) experienced the largest increase (18%) in numbers of HIV diagnoses among all racial/ethnic groups. In 2016, the Centers for Disease Control and Prevention (CDC) assembled a team of scientists and public health analysts to develop a programmatic approach for addressing the increasing HIV diagnosis among Hispanic/Latino MSM. The team used a data driven review process, i.e., comprehensive review of ...

Evaluation of an active decision support system for hemodynamic optimization during elective major vascular surgery.

Active decision support systems implementing goal directed therapy may be an approach to reduce disparities in outcome between different health care providers. We assessed feasibility of and adherence to an active decision support system (ADSS) comprising fluids, vasopressors, and dobutamine to optimize hemodynamics during high-risk vascular surgery.

Suicidal ideation and behaviors within the school context: Perceived teacher, peer and parental support.

School-related factors have been found to be associated with adolescents' suicidal ideation and behaviors, including teacher and peer support. Research has tended to ignore the nested nature of school-related data, which may be critical in this context. The current study implemented a multi-level approach on data from the 2013-14 Health Behaviors in School-aged Children (HBSC-WHO) Israeli survey among high school children (N = 4241; 56% female). Participants completed measures of teacher-, peer-, and pa...

Community-Driven Data Analysis Training for Biology.

The primary problem with the explosion of biomedical datasets is not the data, not computational resources, and not the required storage space, but the general lack of trained and skilled researchers to manipulate and analyze these data. Eliminating this problem requires development of comprehensive educational resources. Here we present a community-driven framework that enables modern, interactive teaching of data analytics in life sciences and facilitates the development of training materials. The key fea...

Controlled feature selection and compressive big data analytics: Applications to biomedical and health studies.

The theoretical foundations of Big Data Science are not fully developed, yet. This study proposes a new scalable framework for Big Data representation, high-throughput analytics (variable selection and noise reduction), and model-free inference. Specifically, we explore the core principles of distribution-free and model-agnostic methods for scientific inference based on Big Data sets. Compressive Big Data analytics (CBDA) iteratively generates random (sub)samples from a big and complex dataset. This subsamp...

Publisher Correction: ERK-mediated phosphorylation regulates SOX10 sumoylation and targets expression in mutant BRAF melanoma.

In the original version of this Article, financial support was not fully acknowledged. The PDF and HTML versions of the Article have now been corrected to include the following: The National Basic Research Program (2015CB553602 to J.L.), the National Natural Science Foundation of China (31570777, 91649106, 31770917 to J.L.) and Tianjin Applied Basic and Frontier Tech Major Project (12JCZDJC34400 to J.L.) and Tianjin Higher Education Sci-Tech Development Project (20112D05 to J.L.).

Implementing a Transcription Factor Interaction Prediction System Using the GenoMetric Query Language.

Novel technologies and growing interest have resulted in a large increase in the amount of data available for genomics and transcriptomics studies, both in terms of volume and contents. Biology is relying more and more on computational methods to process, investigate, and extract knowledge from this huge amount of data. In this work, we present the TICA web server (available at http://www.gmql.eu/tica/ ), a fast and compact tool developed to support data-driven knowledge discovery in the realm of transcript...

Data-driven gating in PET: Influence of respiratory signal noise on motion resolution.

Data-driven gating (DDG) approaches for positron emission tomography (PET) are interesting alternatives to conventional hardware-based gating methods. In DDG, the measured PET data themselves are utilized to calculate a respiratory signal that is subsequently used for gating purposes. The success of gating is then highly dependent on the statistical quality of the PET data. In this study we investigate how this quality determines signal noise and thus motion resolution in clinical PET scans using a center-o...

Simulation of Patient Flow in Multiple Healthcare Units using Process and Data Mining Techniques for Model Identification.

An approach to building a hybrid simulation of patient flow is introduced with a combination of data-driven methods for automation of model identification. The approach is described with a conceptual framework and basic methods for combination of different techniques. The implementation of the proposed approach for simulation of the acute coronary syndrome (ACS) was developed and used in an experimental study.

A Literature Survey and Experimental Evaluation of the State-of-the-Art in Uplift Modeling: A Stepping Stone Toward the Development of Prescriptive Analytics.

Prescriptive analytics extends on predictive analytics by allowing to estimate an outcome in function of control variables, allowing as such to establish the required level of control variables for realizing a desired outcome. Uplift modeling is at the heart of prescriptive analytics and aims at estimating the net difference in an outcome resulting from a specific action or treatment that is applied. In this article, a structured and detailed literature survey on uplift modeling is provided by identifying a...

Big Data Analytic, Big Step for Patient Management and Care in Puerto Rico.

This letter provides an overview of the application of big data in health care system to improve quality of care, including predictive modelling for risk and resource use, precision medicine and clinical decision support, quality of care and performance measurement, public health and research applications, among others. The author delineates the tremendous potential for big data analytics and discuss how it can be successfully implemented in clinical practice, as an important component of a learning health-...


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