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Authors: Wilfred Bonney ; Alexander Doney and Emily Jefferson

Affiliation: University of Dundee, United Kingdom

ISBN: 978-989-758-010-9

Keyword(s): Clinical Datasets, Biochemistry Dataset, LOINC, Data Mining, Health Data Standard.

Related Ontology Subjects/Areas/Topics: Biomedical Engineering ; Electronic Health Records and Standards ; Evaluation and Use of Healthcare IT ; Health Information Systems ; Semantic Interoperability

Abstract: Harnessing clinical datasets from the repository of electronic health records for research and medical intelligence has become the norm of the 21st century. Clinical datasets present a great opportunity for medical researchers and data analysts to perform cohort selections and data linkages to support better informed clinical decision-making and evidence-based medicine. This paper utilized Logical Observation Identifiers Names and Codes (LOINC®) encoding methodology to encode the biochemistry tests in the anonymized biochemistry dataset obtained from the Health Informatics Centre (HIC) at the University of Dundee. Preliminary results indicated that the encoded dataset was flexible in supporting statistical analysis and data mining techniques. Moreover, the results indicated that the LOINC codes cover most of the biochemistry tests used in National Health Service (NHS) Tayside, Scotland.

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Paper citation in several formats:
Bonney W., Doney A. and Jefferson E. (2014). Standardizing Biochemistry Dataset for Medical Research.In Proceedings of the International Conference on Health Informatics - Volume 1: HEALTHINF, (BIOSTEC 2014) ISBN 978-989-758-010-9, pages 205-210. DOI: 10.5220/0004745802050210

author={Wilfred Bonney and Alexander Doney and Emily Jefferson},
title={Standardizing Biochemistry Dataset for Medical Research},
booktitle={Proceedings of the International Conference on Health Informatics - Volume 1: HEALTHINF, (BIOSTEC 2014)},


JO - Proceedings of the International Conference on Health Informatics - Volume 1: HEALTHINF, (BIOSTEC 2014)
TI - Standardizing Biochemistry Dataset for Medical Research
SN - 978-989-758-010-9
AU - Bonney W.
AU - Doney A.
AU - Jefferson E.
PY - 2014
SP - 205
EP - 210
DO - 10.5220/0004745802050210

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