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Prioritizing a high posterior probability threshold leading to low error rate over high classification accuracy: the validity of MorphoPASSE software for cranial morphological sex estimation in a contemporary population
A. Pilmann Kotěrová, F. Santos, Š. Bejdová, R. Rmoutilová, MH. Attia, A. Habiba, J. Velemínská, J. Brůžek
Language English Country Germany
Document type Journal Article, Validation Study
NLK
ProQuest Central
from 1997-02-01 to 1 year ago
Medline Complete (EBSCOhost)
from 2009-07-01 to 1 year ago
Health & Medicine (ProQuest)
from 1997-02-01 to 1 year ago
- MeSH
- Adult MeSH
- Skull * anatomy & histology diagnostic imaging MeSH
- Middle Aged MeSH
- Humans MeSH
- Young Adult MeSH
- Tomography, X-Ray Computed MeSH
- Probability MeSH
- Reproducibility of Results MeSH
- Software * MeSH
- Forensic Anthropology * methods MeSH
- Sex Determination by Skeleton * methods MeSH
- Imaging, Three-Dimensional MeSH
- Check Tag
- Adult MeSH
- Middle Aged MeSH
- Humans MeSH
- Young Adult MeSH
- Male MeSH
- Female MeSH
- Publication type
- Journal Article MeSH
- Validation Study MeSH
- Geographicals
- Egypt MeSH
- France MeSH
An increasing number of software tools can be used in forensic anthropology to estimate a biological profile, but further studies in other populations are required for more robust validation. The present study aimed to evaluate the validity of MorphoPASSE software for sex estimation from sexually dimorphic cranial traits recorded on 3D CT models (n = 180) from three populations samples (Czech, French, and Egyptian). Two independent observers performed scoring of 4 cranial traits (2 of them bilateral) in each population sample of 30 males and 30 females. The accuracy of sex estimation using traditional posterior probability threshold (pp = 0.5) ranged from 85.6% to 88.3% and overall classification error from 14.4% to 11.7% for both observers, and corresponds to the previously published values of the method. The MorphoPASSE method is also affected by the subjectivity of the observers, as both observers show agreement in sex assignment in 83.9% of cases, regardless of the accuracy of the estimates. Applying a higher posterior probability threshold (pp 0.95) provided classification accuracy of 97.9% and 93.3% of individuals (for observer A and B respectively), minimizing the risk of error to 2.1% and 6.7%, respectively. However, sex estimation can only be applied to 54% and 66% of individuals, respectively. Our results demonstrate the validity of the MorphoPASSE software for cranial sex estimation outside the reference population. However, the achieved classification success is accompanied by a high risk of errors, the reduction of which is only possible by increasing the posterior probability threshold.
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