Literature DB >> 27442198

Big Data and Disease Prevention: From Quantified Self to Quantified Communities.

Meredith A Barrett1,2, Olivier Humblet1,2, Robert A Hiatt3, Nancy E Adler1.   

Abstract

Big data is often discussed in the context of improving medical care, but it also has a less appreciated but equally important role to play in preventing disease. Big data can facilitate action on the modifiable risk factors that contribute to a large fraction of the chronic disease burden, such as physical activity, diet, tobacco use, and exposure to pollution. It can do so by facilitating the discovery of risk factors for disease at population, subpopulation, and individual levels, and by improving the effectiveness of interventions to help people achieve healthier behaviors in healthier environments. In this article, we describe new sources of big data in population health, explore their applications, and present two case studies illustrating how big data can be leveraged for prevention. We also discuss the many implementation obstacles that must be overcome before this vision can become a reality.

Entities:  

Year:  2013        PMID: 27442198     DOI: 10.1089/big.2013.0027

Source DB:  PubMed          Journal:  Big Data        ISSN: 2167-6461            Impact factor:   2.128


  24 in total

1.  Big Data, Large-Scale Text Analysis, and Public Health Research.

Authors:  Merlin Chowkwanyun
Journal:  Am J Public Health       Date:  2019-02       Impact factor: 9.308

2.  Commentary: In the Rising Era of Big Data, Small Steps are Key.

Authors:  Nina Heller; Jonathan H Seltzer
Journal:  Ethn Dis       Date:  2017-04-20       Impact factor: 1.847

Review 3.  Big Data in Science and Healthcare: A Review of Recent Literature and Perspectives. Contribution of the IMIA Social Media Working Group.

Authors:  M M Hansen; T Miron-Shatz; A Y S Lau; C Paton
Journal:  Yearb Med Inform       Date:  2014-08-15

4.  A proposed national research and development agenda for population health informatics: summary recommendations from a national expert workshop.

Authors:  Hadi Kharrazi; Elyse C Lasser; William A Yasnoff; John Loonsk; Aneel Advani; Harold P Lehmann; David C Chin; Jonathan P Weiner
Journal:  J Am Med Inform Assoc       Date:  2016-03-27       Impact factor: 4.497

5.  Need for Enhanced Environmental Representation in the Implementation of One Health.

Authors:  Meredith A Barrett; Timothy A Bouley
Journal:  Ecohealth       Date:  2014-09-19       Impact factor: 3.184

Review 6.  The Promise of Digital Health: Then, Now, and the Future.

Authors:  Amy Abernethy; Laura Adams; Meredith Barrett; Christine Bechtel; Patricia Brennan; Atul Butte; Judith Faulkner; Elaine Fontaine; Stephen Friedhoff; John Halamka; Michael Howell; Kevin Johnson; Peter Long; Deven McGraw; Redonda Miller; Peter Lee; Jonathan Perlin; Donald Rucker; Lew Sandy; Lucia Savage; Lisa Stump; Paul Tang; Eric Topol; Reed Tuckson; Kristen Valdes
Journal:  NAM Perspect       Date:  2022-06-27

7.  A generic method for improving the spatial interoperability of medical and ecological databases.

Authors:  A Ghenassia; J B Beuscart; G Ficheur; F Occelli; E Babykina; E Chazard; M Genin
Journal:  Int J Health Geogr       Date:  2017-10-03       Impact factor: 3.918

Review 8.  Towards Personal Exposures: How Technology Is Changing Air Pollution and Health Research.

Authors:  A Larkin; P Hystad
Journal:  Curr Environ Health Rep       Date:  2017-12

9.  Adolescent HIV-related behavioural prediction using machine learning: a foundation for precision HIV prevention.

Authors:  Bo Wang; Feifan Liu; Lynette Deveaux; Arlene Ash; Samiran Gosh; Xiaoming Li; Elke Rundensteiner; Lesley Cottrell; Richard Adderley; Bonita Stanton
Journal:  AIDS       Date:  2021-05-01       Impact factor: 4.177

10.  Data Talks: Obesity-Related Influences on US Mortality Rates.

Authors:  Malcolm J D'Souza; Riza C Bautista; Derald E Wentzien
Journal:  Res Health Sci       Date:  2018
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