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Letter to the editor: robustness of osteoporosis risk prediction models with enhanced statistical analyses

2025-09Carta ao editor Acesso restrito
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datacite.subject.sdg03:Saúde de Qualidade
datacite.subject.sdg09:Indústria, Inovação e Infraestruturas
datacite.subject.sdg10:Reduzir as Desigualdades
dc.contributor.authorPires de Carvalho, Filipe Ricardo
dc.contributor.authorGavaia, Paulo
dc.date.accessioned2026-03-26T10:01:01Z
dc.date.available2026-03-26T10:01:01Z
dc.date.issued2025-09
dc.description.abstractIn response to Oka et al.’s letter, we conducted additional statistical analyses to validate the robustness of our osteoporosis risk prediction model using NHANES 2007–2014 data (n = 7924). We evaluated 10 key predictors through Spearman’s rho, Kendall’s tau, Mutual Information (MI), and Total Correlation. Weight (BMX_BMXWT) and arm circumference (BMX_BMXARMC) showed strong negative correlations with osteoporosis risk (rho: 0.49, 􀀀 0.47, p < 1e-270; MI: 0.17, 0.15), while age (DEMO_RIDAGEYR) exhibited a positive correlation (rho: 0.33, p < 1e-128; MI: 0.08). Total Correlation (32.68) confirmed significant multivariate interactions among predictors. These findings reinforce the model’s predictive strength, addressing Oka et al.’s recommendations and affirming the importance of anthropometric and demographic factors in osteoporosis risk assessment.eng
dc.identifier.doi10.1016/j.compbiomed.2025.110711
dc.identifier.issn0010-4825
dc.identifier.urihttp://hdl.handle.net/10400.1/28549
dc.language.isoeng
dc.peerreviewedyes
dc.publisherElsevier
dc.relationAlgarve Centre for Marine Sciences
dc.relationCentre for Marine and Environmental Research
dc.relation.ispartofComputers in Biology and Medicine
dc.rights.uriN/A
dc.subjectOsteoporosis risk prediction
dc.subjectMachine learning
dc.subjectFeature importance
dc.subjectStatistical validation
dc.subjectSpearman’s rho
dc.subjectKendall’s tau
dc.subjectMutual information
dc.subjectTotal correlation
dc.subjectNHANES 2007-2014
dc.subjectStacking ensemble
dc.titleLetter to the editor: robustness of osteoporosis risk prediction models with enhanced statistical analyseseng
dc.typeletter to the editor
dspace.entity.typePublication
oaire.awardNumberUIDP/04326/2020
oaire.awardNumberLA/P/0101/2020
oaire.awardTitleAlgarve Centre for Marine Sciences
oaire.awardTitleCentre for Marine and Environmental Research
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDP%2F04326%2F2020/PT
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/LA%2FP%2F0101%2F2020/PT
oaire.citation.issuePart. A
oaire.citation.startPage110711
oaire.citation.titleComputers in Biology and Medicine
oaire.citation.volume196
oaire.fundingStream6817 - DCRRNI ID
oaire.fundingStream6817 - DCRRNI ID
oaire.versionhttp://purl.org/coar/version/c_970fb48d4fbd8a85
person.familyNamePires de Carvalho
person.familyNameGavaia
person.givenNameFilipe Ricardo
person.givenNamePaulo
person.identifier.ciencia-id181A-A440-7D6E
person.identifier.ciencia-idB619-FC16-D007
person.identifier.orcid0000-0002-1468-0305
person.identifier.orcid0000-0002-9582-1957
person.identifier.ridA-6470-2011
person.identifier.scopus-author-id55115644400
person.identifier.scopus-author-id6507104377
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
relation.isAuthorOfPublication55c2b5fb-f39a-4675-834a-f44c5fe417aa
relation.isAuthorOfPublication9dca2139-21a4-4d59-aaf7-531f1033a58e
relation.isAuthorOfPublication.latestForDiscovery55c2b5fb-f39a-4675-834a-f44c5fe417aa
relation.isProjectOfPublication15f91d45-e070-47d8-b6b8-efd4de31d9a8
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