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8 results on '"Data Mining trends"'

1. Extension of research data repository system to support direct compute access to biomedical datasets: enhancing Dataverse to support large datasets.

Author

McKinney B, Meyer PA, Crosas M, and Sliz P

Subjects
Animals, Computational Biology instrumentation, Computational Biology trends, Crystallography, X-Ray, Data Mining trends, Humans, Image Interpretation, Computer-Assisted, Internet, Periodicals as Topic, Protein Conformation, Software, Access to Information, Biomedical Research trends, Computational Biology methods, Computer Communication Networks instrumentation, Computer Communication Networks trends, Database Management Systems trends, Databases, Protein trends
Abstract

Access to experimental X-ray diffraction image data is important for validation and reproduction of macromolecular models and indispensable for the development of structural biology processing methods. In response to the evolving needs of the structural biology community, we recently established a diffraction data publication system, the Structural Biology Data Grid (SBDG, data.sbgrid.org), to preserve primary experimental datasets supporting scientific publications. All datasets published through the SBDG are freely available to the research community under a public domain dedication license, with metadata compliant with the DataCite Schema (schema.datacite.org). A proof-of-concept study demonstrated community interest and utility. Publication of large datasets is a challenge shared by several fields, and the SBDG has begun collaborating with the Institute for Quantitative Social Science at Harvard University to extend the Dataverse (dataverse.org) open-source data repository system to structural biology datasets. Several extensions are necessary to support the size and metadata requirements for structural biology datasets. In this paper, we describe one such extension-functionality supporting preservation of file system structure within Dataverse-which is essential for both in-place computation and supporting non-HTTP data transfers., (© 2016 New York Academy of Sciences.)

Published
2017
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2. Distributed data networks: a blueprint for Big Data sharing and healthcare analytics.

Author

Popovic JR

Subjects
Algorithms, Computational Biology instrumentation, Computational Biology trends, Data Mining trends, Database Management Systems instrumentation, Database Management Systems trends, Decision Making, Computer-Assisted, Humans, Machine Learning, Medical Informatics instrumentation, Medical Informatics methods, Medical Informatics trends, United States, United States Food and Drug Administration, Access to Information, Computational Biology methods, Computer Communication Networks instrumentation, Computer Communication Networks trends, Data Mining methods, Sentinel Surveillance
Abstract

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. This paper also introduces one use case for machine learning algorithm development to fully utilize and advance the portfolio of population health analytics, particularly those using multisite administrative data sources., (© 2016 New York Academy of Sciences.)

Published
2017
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3. Big Data and paediatric cardiovascular disease in the era of transparency in healthcare.

Author

Asante-Korang A and Jacobs JP

Subjects
Databases as Topic, Humans, Access to Information, Cardiovascular Diseases, Data Mining trends, Delivery of Health Care, Pediatrics
Abstract

The objectives of this review were to discuss the potential impact of Big Data analytics in paediatric cardiovascular disease and its potential to address the challenges of transparency in delivery of care to this unique population.

Published
2016
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4. Acquisition, Analysis, and Sharing of Data in 2015 and Beyond: A Survey of the Landscape: A Conference Report From the American Heart Association Data Summit 2015.

Author

Antman EM, Benjamin EJ, Harrington RA, Houser SR, Peterson ED, Bauman MA, Brown N, Bufalino V, Califf RM, Creager MA, Daugherty A, Demets DL, Dennis BP, Ebadollahi S, Jessup M, Lauer MS, Lo B, MacRae CA, McConnell MV, McCray AT, Mello MM, Mueller E, Newburger JW, Okun S, Packer M, Philippakis A, Ping P, Prasoon P, Roger VL, Singer S, Temple R, Turner MB, Vigilante K, Warner J, and Wayte P

Subjects
American Heart Association, Biomedical Research trends, Cardiology trends, Consensus, Cooperative Behavior, Diffusion of Innovation, Forecasting, Humans, Interdisciplinary Communication, United States, Access to Information, Biomedical Research organization & administration, Cardiology organization & administration, Cardiovascular Diseases diagnosis, Cardiovascular Diseases etiology, Cardiovascular Diseases therapy, Data Mining trends, Databases, Factual trends, Information Dissemination, Stroke diagnosis, Stroke etiology, Stroke therapy
Abstract

Background: A 1.5-day interactive forum was convened to discuss critical issues in the acquisition, analysis, and sharing of data in the field of cardiovascular and stroke science. The discussion will serve as the foundation for the American Heart Association's (AHA's) near-term and future strategies in the Big Data area. The concepts evolving from this forum may also inform other fields of medicine and science., Methods and Results: A total of 47 participants representing stakeholders from 7 domains (patients, basic scientists, clinical investigators, population researchers, clinicians and healthcare system administrators, industry, and regulatory authorities) participated in the conference. Presentation topics included updates on data as viewed from conventional medical and nonmedical sources, building and using Big Data repositories, articulation of the goals of data sharing, and principles of responsible data sharing. Facilitated breakout sessions were conducted to examine what each of the 7 stakeholder domains wants from Big Data under ideal circumstances and the possible roles that the AHA might play in meeting their needs. Important areas that are high priorities for further study regarding Big Data include a description of the methodology of how to acquire and analyze findings, validation of the veracity of discoveries from such research, and integration into investigative and clinical care aspects of future cardiovascular and stroke medicine. Potential roles that the AHA might consider include facilitating a standards discussion (eg, tools, methodology, and appropriate data use), providing education (eg, healthcare providers, patients, investigators), and helping build an interoperable digital ecosystem in cardiovascular and stroke science., Conclusion: There was a consensus across stakeholder domains that Big Data holds great promise for revolutionizing the way cardiovascular and stroke research is conducted and clinical care is delivered; however, there is a clear need for the creation of a vision of how to use it to achieve the desired goals. Potential roles for the AHA center around facilitating a discussion of standards, providing education, and helping establish a cardiovascular digital ecosystem. This ecosystem should be interoperable and needs to interface with the rapidly growing digital object environment of the modern-day healthcare system., (© 2015 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley Blackwell.)

Published
2015
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5. Elsevier opens its papers to text-mining.

Author

Van Noorden R

Subjects
Copyright ethics, Copyright legislation & jurisprudence, Humans, Research Personnel, Access to Information, Data Mining trends, Periodicals as Topic, Publishing, Research
Published
2014
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7. Trouble at the text mine.

Author

Van Noorden R

Subjects
Data Mining legislation & jurisprudence, Genomics, Humans, Molecular Sequence Annotation trends, Publishing trends, Research trends, Access to Information legislation & jurisprudence, Data Mining trends, Molecular Sequence Annotation methods, Periodicals as Topic, Research Design
Published
2012
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8. Gold in the text?

Subjects
Drug Discovery methods, Publishing legislation & jurisprudence, Publishing trends, Software trends, Access to Information legislation & jurisprudence, Computers statistics & numerical data, Data Mining statistics & numerical data, Data Mining trends
Published
2012
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