Literature DB >> 25910540

Big Data Technologies: New Opportunities for Diabetes Management.

Riccardo Bellazzi1, Arianna Dagliati2, Lucia Sacchi2, Daniele Segagni3.   

Abstract

The so-called big data revolution provides substantial opportunities to diabetes management. At least 3 important directions are currently of great interest. First, the integration of different sources of information, from primary and secondary care to administrative information, may allow depicting a novel view of patient's care processes and of single patient's behaviors, taking into account the multifaceted nature of chronic care. Second, the availability of novel diabetes technologies, able to gather large amounts of real-time data, requires the implementation of distributed platforms for data analysis and decision support. Finally, the inclusion of geographical and environmental information into such complex IT systems may further increase the capability of interpreting the data gathered and extract new knowledge from them. This article reviews the main concepts and definitions related to big data, it presents some efforts in health care, and discusses the potential role of big data in diabetes care. Finally, as an example, it describes the research efforts carried on in the MOSAIC project, funded by the European Commission.
© 2015 Diabetes Technology Society.

Entities:  

Keywords:  big data; data analytics; data integration; diabetes mellitus; information technology

Mesh:

Year:  2015        PMID: 25910540      PMCID: PMC4667334          DOI: 10.1177/1932296815583505

Source DB:  PubMed          Journal:  J Diabetes Sci Technol        ISSN: 1932-2968


  37 in total

1.  Exposome informatics: considerations for the design of future biomedical research information systems.

Authors:  Fernando Martin Sanchez; Kathleen Gray; Riccardo Bellazzi; Guillermo Lopez-Campos
Journal:  J Am Med Inform Assoc       Date:  2013-11-01       Impact factor: 4.497

2.  Analyzing complex patients' temporal histories: new frontiers in temporal data mining.

Authors:  Lucia Sacchi; Arianna Dagliati; Riccardo Bellazzi
Journal:  Methods Mol Biol       Date:  2015

Review 3.  Big data, smart homes and ambient assisted living.

Authors:  V Vimarlund; S Wass
Journal:  Yearb Med Inform       Date:  2014-08-15

4.  Learning from big health care data.

Authors:  Sebastian Schneeweiss
Journal:  N Engl J Med       Date:  2014-06-05       Impact factor: 91.245

5.  The use of sequential pattern mining to predict next prescribed medications.

Authors:  Aileen P Wright; Adam T Wright; Allison B McCoy; Dean F Sittig
Journal:  J Biomed Inform       Date:  2014-09-16       Impact factor: 6.317

6.  Exploration of patterns predicting renal damage in patients with diabetes type II using a visual temporal analysis laboratory.

Authors:  Denis Klimov; Alexander Shknevsky; Yuval Shahar
Journal:  J Am Med Inform Assoc       Date:  2014-10-28       Impact factor: 4.497

7.  Challenges and future directions of the T1D Exchange Clinic Network and registry.

Authors:  Kellee M Miller; Dongyuan Xing; William V Tamborlane; Richard M Bergenstal; Roy W Beck
Journal:  J Diabetes Sci Technol       Date:  2013-07-01

Review 8.  Applications of the MapReduce programming framework to clinical big data analysis: current landscape and future trends.

Authors:  Emad A Mohammed; Behrouz H Far; Christopher Naugler
Journal:  BioData Min       Date:  2014-10-29       Impact factor: 2.522

9.  Big data and ambulatory care: breaking down legal barriers to support effective use.

Authors:  Jane Hyatt Thorpe; Elizabeth Alexandra Gray
Journal:  J Ambul Care Manage       Date:  2015 Jan-Mar

10.  NCBI's Database of Genotypes and Phenotypes: dbGaP.

Authors:  Kimberly A Tryka; Luning Hao; Anne Sturcke; Yumi Jin; Zhen Y Wang; Lora Ziyabari; Moira Lee; Natalia Popova; Nataliya Sharopova; Masato Kimura; Michael Feolo
Journal:  Nucleic Acids Res       Date:  2013-12-01       Impact factor: 16.971

View more
  6 in total

1.  Clinical Research Informatics Contributions from 2015.

Authors:  C Daniel; R Choquet
Journal:  Yearb Med Inform       Date:  2016-11-10

Review 2.  A Digital Ecosystem of Diabetes Data and Technology: Services, Systems, and Tools Enabled by Wearables, Sensors, and Apps.

Authors:  Nathaniel D Heintzman
Journal:  J Diabetes Sci Technol       Date:  2015-12-20

3.  Continuous Glucose Monitoring: Current Use in Diabetes Management and Possible Future Applications.

Authors:  Martina Vettoretti; Giacomo Cappon; Giada Acciaroli; Andrea Facchinetti; Giovanni Sparacino
Journal:  J Diabetes Sci Technol       Date:  2018-05-22

4.  Integration of Administrative, Clinical, and Environmental Data to Support the Management of Type 2 Diabetes Mellitus: From Satellites to Clinical Care.

Authors:  Arianna Dagliati; Andrea Marinoni; Carlo Cerra; Pasquale Decata; Luca Chiovato; Paolo Gamba; Riccardo Bellazzi
Journal:  J Diabetes Sci Technol       Date:  2015-12-01

5.  Digital Diabetes Data and Artificial Intelligence: A Time for Humility Not Hubris.

Authors:  David Kerr; David C Klonoff
Journal:  J Diabetes Sci Technol       Date:  2018-09-05

Review 6.  Continuous Glucose Monitoring in Healthy Adults-Possible Applications in Health Care, Wellness, and Sports.

Authors:  Roman Holzer; Wilhelm Bloch; Christian Brinkmann
Journal:  Sensors (Basel)       Date:  2022-03-05       Impact factor: 3.576

  6 in total

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