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Publication details

Document type
Journal articles

Document subtype
Full paper

Title
Machine learning modelling of blood lipid biomarkers in familial hypercholesterolaemia versus polygenic/environmental dyslipidaemia

Participants in the publication
Marta Correia (Author)
Eva Kagenaar (Author)
Daniël Bernardus van Schalkwijk (Author)
Mafalda Bourbon (Author)
Margarida Gama-Carvalho (Author)
Dep. Química e Bioquímica
 BioISI
Date of Publication
2021-02-15

Where published
Scientific Reports

Publication Identifiers
ISSN - 2045-2322

Publisher
Springer Science and Business Media LLC

Volume
11
Number
1

Document Identifiers
DOI - https://doi.org/10.1038/s41598-021-83392-w
URL - http://dx.doi.org/10.1038/s41598-021-83392-w

Rankings
Web Of Science Q1 (2020) - 4.38 - MULTIDISCIPLINARY SCIENCES - SCIE
SCOPUS Q1 (2020) - 7.1 - Multidisciplinary


Export

APA
Marta Correia, Eva Kagenaar, Daniël Bernardus van Schalkwijk, Mafalda Bourbon, Margarida Gama-Carvalho, (2021). Machine learning modelling of blood lipid biomarkers in familial hypercholesterolaemia versus polygenic/environmental dyslipidaemia. Scientific Reports, 11, ISSN 2045-2322. eISSN . http://dx.doi.org/10.1038/s41598-021-83392-w

IEEE
Marta Correia, Eva Kagenaar, Daniël Bernardus van Schalkwijk, Mafalda Bourbon, Margarida Gama-Carvalho, "Machine learning modelling of blood lipid biomarkers in familial hypercholesterolaemia versus polygenic/environmental dyslipidaemia" in Scientific Reports, vol. 11, 2021. 10.1038/s41598-021-83392-w

BIBTEX
@article{55256, author = {Marta Correia and Eva Kagenaar and Daniël Bernardus van Schalkwijk and Mafalda Bourbon and Margarida Gama-Carvalho}, title = {Machine learning modelling of blood lipid biomarkers in familial hypercholesterolaemia versus polygenic/environmental dyslipidaemia}, journal = {Scientific Reports}, year = 2021, volume = 11 }