Identifying clinically important COPD sub-types using data-driven approaches in primary care population based electronic health records-Reference-Cited by-同舟云学术

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Identifying clinically important COPD sub-types using data-driven approaches in primary care population based electronic health records

Published:2019-04-18 Issue:1 Volume:19 Page:
ISSN:1472-6947
Container-title:BMC Medical Informatics and Decision Making
language:en
Short-container-title:BMC Med Inform Decis Mak

Author:

Pikoula Maria^ORCID,Quint Jennifer Kathleen,Nissen Francis,Hemingway Harry,Smeeth Liam,Denaxas Spiros

Funder

National Institute for Health Research

Wellcome Trust

Medical Research Council

British Lung Foundation

Publisher

Springer Science and Business Media LLC

Subject

Health Informatics,Health Policy,Computer Science Applications

Link

http://link.springer.com/content/pdf/10.1186/s12911-019-0805-0.pdf

Reference38 articles.

1. Mathers CD, Loncar D. Projections of global mortality and burden of disease from 2002 to 2030. PLoS Med. 2006;3:e442.

2. Soriano JB. An epidemiological Overview of chronic obstructive pulmonary disease: what can real-life data tell us about disease management? COPD J Chron Obstruct Pulmon Dis. 2017;14:S3–7.

3. Rothnie KJ, et al. Recording of hospitalizations for acute exacerbations of COPD in UK electronic health care records. Clin Epidemiol. 2016;8:771–82.

4. Woodruff PG, Agusti A, Roche N, Singh D, Martinez FJ. Chronic obstructive pulmonary disease 2 current concepts in targeting chronic obstructive pulmonary disease pharmacotherapy: making progress towards personalised management; 2015. p. 385. https://doi.org/10.1016/S0140-6736(15)60693-6

5. Agusti A, Agustí A. The path to personalised medicine in. COPD. 2014. https://doi.org/10.1136/thoraxjnl-2014-205507 .

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