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Deriving research-quality phenotypes from national electronic health records to advance precision medicine: a UK Biobank case-study

Denaxas, SC; Fatemifar, G; Patel, R; Hemingway, H; (2017) Deriving research-quality phenotypes from national electronic health records to advance precision medicine: a UK Biobank case-study. In: Proceedings of the BHI-2017 International Conference on Biomedical and Health Informatics. IEEE Engineering in Medicine and Biology Society (EMBS): Orlando, FL, USA. Green open access

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Abstract

High-throughput genotyping and increased availability of electronic health records (EHR) are giving scientists the unprecedented opportunity to exploit routinely generated clinical data to advance precision medicine. The extent to which national structured EHR in the United Kingdom can be utilized in genome-wide association studies (GWAS) has not been systematically examined. In this study, we evaluate the performance of an EHR-derived acute myocardial infarction phenotype (AMI) for performing GWAS in the UK Biobank.

Type: Proceedings paper
Title: Deriving research-quality phenotypes from national electronic health records to advance precision medicine: a UK Biobank case-study
Event: BHI-2017 International Conference on Biomedical and Health Informatics
Open access status: An open access version is available from UCL Discovery
Publisher version: https://bhi.embs.org/2017/
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
UCL classification: UCL > School of Life and Medical Sciences
UCL > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute of Cardiovascular Science
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URI: http://discovery.ucl.ac.uk/id/eprint/1542412
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