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Sex estimation with the total area of the proximal femur: A densitometric approach

2017-06Journal article Restricted
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dc.contributor.authorCurate, Francisco
dc.contributor.authorAlbuquerque, Anabela
dc.contributor.authorFerreira, Izilda
dc.contributor.authorCunha, Eugenia
dc.date.accessioned2019-11-20T15:07:33Z
dc.date.available2019-11-20T15:07:33Z
dc.date.issued2017-06
dc.description.abstractThe estimation of sex is a central step to establish the biological profile of an anonymous skeletal individual. Imaging techniques, including bone densitometry, have been used to evaluate sex in remains incompletely skeletonized. In this paper, we present a technique for sex estimation using the total area (TA) of the proximal femur, a two-dimensional areal measurement determined through densitometry. TA was acquired from a training sample (112 females; 112 males) from the Coimbra Identified Skeletal Collection (University of Coimbra, Portugal). Logistic regression (LR), linear discriminant analysis (LDA), reduce error pruning trees (REPTree), and classification and regression trees (CART) were employed in order to obtain models that could predict sex in unidentified skeletal remains. Under cross-validation, the proposed models correctly estimated sex in 90.2-92.0% of cases (bias ranging from 1.8% to 4.5%). The models were evaluated in an independent test sample (30 females; 30 males) from the 21st Century Identified Skeletal Collection (University of Coimbra, Portugal), with a sex allocation accuracy ranging from 90.0% to 91.7% (bias from 3.3% to 10.0%). Overall, data mining classifiers, especially the REPTree, performed better than the traditional classifiers (LR and LDA), maximizing overall accuracy and minimizing bias. This study emphasizes the significant value of bone densitometry to estimate sex in cadaveric remains in diverse states of preservation and completeness, even human remains with soft tissues. (C) 2017 Elsevier B. V. All rights reserved.
dc.description.sponsorshipFundacao para a Ciencia e Tecnologia [SFRH/BPD/74015/2010]
dc.description.versioninfo:eu-repo/semantics/publishedVersion
dc.identifier.doi10.1016/j.forsciint.2017.02.035
dc.identifier.issn0379-0738
dc.identifier.issn1872-6283
dc.identifier.urihttp://hdl.handle.net/10400.1/13102
dc.language.isoeng
dc.peerreviewedyes
dc.publisherElsevier Ireland Ltd
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectForensic anthropology
dc.subjectComputed-tomography
dc.subjectHip bone
dc.subjectSample
dc.subjectRadiographs
dc.subjectPopulation
dc.subjectFracture
dc.subjectDensity
dc.subjectWomen
dc.subjectMen
dc.titleSex estimation with the total area of the proximal femur: A densitometric approach
dc.typejournal article
dspace.entity.typePublication
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/SFRH/SFRH%2FBPD%2F74015%2F2010/PT
oaire.citation.endPage116
oaire.citation.startPage110
oaire.citation.titleForensic Science International
oaire.citation.volume275
oaire.fundingStreamSFRH
person.familyNameTaborda Curate
person.givenNameJosé Francisco
person.identifierhttps://scholar.google.pt/citations?user=rG909IQAAAAJ&hl=pt-PT
person.identifier.ciencia-idEF1B-4B08-5982
person.identifier.orcid0000-0002-0480-209X
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a Ciência e a Tecnologia
rcaap.rightsrestrictedAccess
rcaap.typearticle
relation.isAuthorOfPublication255b6420-8d4b-438d-b232-6ba3d1a1248c
relation.isAuthorOfPublication.latestForDiscovery255b6420-8d4b-438d-b232-6ba3d1a1248c
relation.isProjectOfPublication3c733ef8-a5e9-48a2-803a-049ada08b4de
relation.isProjectOfPublication.latestForDiscovery3c733ef8-a5e9-48a2-803a-049ada08b4de

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