Repository logo
 
Publication

Performance comparison of different classification algorithms applied to the diagnosis of familial hypercholesterolemia in paediatric subjects

2022-01-21Journal article Open access
Simple item page
dc.contributor.authorAlbuquerque, João
dc.contributor.authorMedeiros, Ana Margarida
dc.contributor.authorAlves, Ana Catarina
dc.contributor.authorBourbon, Mafalda
dc.contributor.authorAntunes, Marília
dc.date.accessioned2022-10-31T14:47:46Z
dc.date.available2022-10-31T14:47:46Z
dc.date.issued2022-01-21
dc.descriptionObservational Studypt_PT
dc.description.abstractFamilial Hypercholesterolemia (FH) is an inherited disorder of lipid metabolism, characterized by increased low density lipoprotein cholesterol (LDLc) levels. The main purpose of the current work was to explore alternative classification methods to traditional clinical criteria for FH diagnosis, based on several biochemical and biological indicators. Logistic regression (LR), decision tree (DT), random forest (RF) and naive Bayes (NB) algorithms were developed for this purpose, and thresholds were optimized by maximization of Youden index (YI). All models presented similar accuracy (Acc), specificity (Spec) and positive predictive values (PPV). Sensitivity (Sens) and G-mean values were significantly higher in LR and RF models, compared to the DT. When compared to Simon Broome (SB) biochemical criteria for FH diagnosis, all models presented significantly higher Acc, Spec and G-mean values (p < 0.01), and lower negative predictive value (NPV, p < 0.05). Moreover, LR and RF models presented comparable Sens values. Adjustment of the cut-off point by maximizing YI significantly increased Sens values, with no significant loss in Acc. The obtained results suggest such classification algorithms can be a viable alternative to be used as a widespread screening method. An online application has been developed to assess the performance of the LR model in a wider population.pt_PT
dc.description.sponsorshipNORTE-08-5369-FSE-000018/Horizon 2020 Framework Programme UID/MAT/00006/2019/Fundação para a Ciência e a Tecnologia PTDC/SAU-SER/29180/2017/Fundação para a Ciência e a Tecnologiapt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationSci Rep. 2022 Jan 21;12(1):1164. doi: 10.1038/s41598-022-05063-8pt_PT
dc.identifier.doi10.1038/s41598-022-05063-8pt_PT
dc.identifier.issn2045-2322
dc.identifier.urihttp://hdl.handle.net/10400.18/8288
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherNature Researchpt_PT
dc.relationCentre of Statistics and its Applications
dc.relationDyslipidaemia stratification : new screening tools for a cost effective approach
dc.relation.publisherversionhttps://www.nature.com/articles/s41598-022-05063-8pt_PT
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/pt_PT
dc.subjectFamilial Hypercholesterolemiapt_PT
dc.subjectCholesterolpt_PT
dc.subjectDoenças Cardio e Cérebro-vascularespt_PT
dc.subjectColesterolpt_PT
dc.subjectHipercolesterolemia Familiarpt_PT
dc.titlePerformance comparison of different classification algorithms applied to the diagnosis of familial hypercholesterolemia in paediatric subjectspt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.awardTitleCentre of Statistics and its Applications
oaire.awardTitleDyslipidaemia stratification : new screening tools for a cost effective approach
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UID%2FMAT%2F00006%2F2019/PT
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/3599-PPCDT/PTDC%2FSAU-SER%2F29180%2F2017/PT
oaire.citation.issue1pt_PT
oaire.citation.startPage1164pt_PT
oaire.citation.titleScientific Reportspt_PT
oaire.citation.volume12pt_PT
oaire.fundingStream6817 - DCRRNI ID
oaire.fundingStream3599-PPCDT
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a Ciência e a Tecnologia
project.funder.nameFundação para a Ciência e a Tecnologia
rcaap.embargofctAcesso de acordo com política editorial da revista.pt_PT
rcaap.rightsopenAccesspt_PT
rcaap.typearticlept_PT
relation.isProjectOfPublicationd9faf814-0ee6-4214-92c8-4fd692956da5
relation.isProjectOfPublicationcde71551-1825-44a0-bc4d-e85c0e2955c8
relation.isProjectOfPublication.latestForDiscoverycde71551-1825-44a0-bc4d-e85c0e2955c8

Files

Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
Performance comparison of different classification algorithms applied to the diagnosis of familial hypercholesterolemia in paediatric subjects.pdf
Size:
8.55 MB
Format:
Adobe Portable Document Format
Download
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
1.71 KB
Format:
Item-specific license agreed upon to submission
Description:
Download

Collections

DPSPDNT - Artigos em revistas internacionais