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Outlier removal methods for skewed data: Impact on age-specific high-sensitive cardiac troponin T 99th percentiles
Department of Biochemistry and Molecular Biology, South Lyon Hospital Group, Hospices Civils de Lyon (HCL), 165 Chemin du Grand Revoyet, Pierre-Bénite, 69495, France.
University West, School of Business, Economics and IT, Divison of Informatics.ORCID iD: 0000-0002-0575-4309
Department of Clinical and Exercise Physiology, University Hospital of Saint-Etienne, Saint-Etienne, France; EA 4607 SNA-EPIS, PRES Lyon, Saint-Etienne, France .
Department of Metabolic Biochemistry, La Pitié Salpêtrière-Charles Foix University Hospital (AP-HP), Paris, France; CNRS UMR8258, INSERM U1022, Faculty of Pharmacy, Sorbonne Paris Cité, Paris Descartes University, Paris, France.
2019 (English)In: Clinical Chemistry and Laboratory Medicine, ISSN 1434-6621, E-ISSN 1437-4331, Vol. 57, no 10, p. E244-E247Article in journal, Letter (Refereed) Published
Place, publisher, year, edition, pages
2019. Vol. 57, no 10, p. E244-E247
Keywords [en]
99th percentile; high-sensitive cardiac troponin; nonparametric methods; outlier removal
National Category
Cardiology and Cardiovascular Disease Computer Sciences
Research subject
SOCIAL SCIENCE, Informatics
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URN: urn:nbn:se:hv:diva-13761DOI: 10.1515/cclm-2018-1366ISI: 000486918000002Scopus ID: 2-s2.0-85063076778OAI: oai:DiVA.org:hv-13761DiVA, id: diva2:1316437
Available from: 2019-05-17 Created: 2019-05-17 Last updated: 2025-09-30Bibliographically approved

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