Forensic Odontology

Edgar, Heather J. H.; Rautman, Anna L.M.

doi:10.1002/9781118845486.ch21

Cited by 4 publications

(5 citation statements)

References 95 publications

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“…A partial-least-square (PLS) analysis was then performed to study the variance of the Procrustes superimposition, and an ANN was applied to cope with the required computations and analysis. In fact, the previous literature has demonstrated that GMA combined with an ANN can be used to obtain better prediction for species classifications [ 26 ], especially if dimensionality reduction is performed [ 31 ]. Therefore, we used GMA to obtain shape data from the sample, a PLS analysis to reduce the dimensionality of the data, and a multilayer perceptron type of ANN in order to obtain a better classification of the sample.…”

Section: Discussionmentioning

confidence: 99%

“…The “set-aside” approach was used to assess the accuracy of the proposed neural networks [ 20 , 31 ] by diving the sample into two subgroups: the training sample (75 casts) used to build the ANN and the test sample (25 casts), on which the obtained ANN was applied in order to measure its performance in predicting sex. For sex classification, two variables were used as input variables (predictors) in the ANN: the first axis of the PLS analysis and the centroid size.…”

Section: Methodsmentioning

confidence: 99%

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Three-Dimensional Dental Analysis for Sex Estimation in the Italian Population: A Pilot Study Based on a Geometric Morphometric and Artificial Neural Network Approach

et al. 2021

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Dental dimorphism can be used for discriminating sex in forensic contexts. Geometric morphometric analysis (GMA) allows the evaluation of the shape and size, separately, of uneven 3D objects. This study presents experiments using a novel combination of GMA and an artificial neural network (ANN) for sex classification, applied to premolars of Caucasian Italian adults (50 females and 50 males). General Procrustes superimposition (GPS) and the partial least square (PLS) method were performed, respectively, to study the shape variance between sexes and to eliminate landmark variations. The “set-aside” approach was used to assess the accuracy of the proposed neural networks. As the main findings of the pilot study, the proposed method applied to the first upper premolar correctly classified 90% of females and 73% of males of the test sample. The accuracy was 0.84 and 0.80 for the training and test samples, respectively. The sexual dimorphism resulting from GMA was low, although statistically significant. GMA combined with the ANN demonstrated better sex classification ability than previous odontometric or dental morphometric methods. Future research could overcome some limitations by considering a larger sample of subjects and other kinds of teeth and experimenting with the use of computer vision for automatic landmark positioning.

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Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Three-Dimensional Dental Analysis for Sex Estimation in the Italian Population: A Pilot Study Based on a Geometric Morphometric and Artificial Neural Network Approach

et al. 2021

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“…The results are favorable to those reported using cusp tip location in molars (Kenyhercz, Klales & Kenyhercz, ), suggesting that geometric morphometric shape analysis of premolars (particularly the upper premolars) may provide an additional avenue to explore divergence between different world populations. Future studies may utilize a “set‐aside” group to assess the accuracy of generated discriminant functions for forensic application (Edgar & Rautman, ).…”

Section: Discussionmentioning

confidence: 99%

Three‐dimensional (3D) geometric morphometric analysis of human premolars to assess sexual dimorphism and biological ancestry in Australian populations

Yong

Ranjitkar

Lekkas

et al. 2018

American J Phys Anthropol

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“…The “set-aside” approach was used to assess the accuracy of the proposed ANN [ 25 , 37 ] by diving the sample into two subgroups: the training sample (174 scans, 84 F and 90 M) used to build the ANN and the test sample (56 scans, 31 F e 25 M), on which the obtained ANN was applied in order to measure its performance in predicting sex.…”

Section: Methodsmentioning

confidence: 99%

A Semi-Automatic Method on a Small Italian Sample for Estimating Sex Based on the Shape of the Crown of the Maxillary Posterior Teeth

et al. 2023

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Teeth are known to be reliable substrates for human identification and are endowed with significant sexual dimorphism not only in the size but also in the shape of the crowns. In the preliminary phase of our study (already published in 2021), a novel sex estimation method based on dental morphometric geometric (GMA) analysis combined with the artificial neural network (ANN) was developed and validated on a single dental element (first upper premolar) with an accuracy rate of 80%. This study aims to experiment and validate the combination of GMA-ANN on the upper first and second left premolars and the upper left first molar to obtain a reliable classification model based on the sexual dimorphic traits of multiple maxillary teeth of Caucasian Italian adults (115 males and 115 females). A general procrustes superimposition (GPS) and principal component analysis (PCA) were performed to study the shape variance between the sexes and to reduce the data variations. The “set-aside” approach was used to validate the accuracy of the proposed ANN. As the main findings, the proposed method correctly classified 94% of females and 68% of males from the test sample and the overall accuracy gained was 82%, higher than the odontometric methods that similarly consider multiple teeth. The shape variation between male and female premolars represents the best dimorphic feature compared with the first upper molar. Future research could overcome some limitations by considering a larger sample of subjects and experimenting with the use of computer vision for automatic landmark positioning and should verify the present evidence in samples with different ancestry.

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Forensic Odontology

Cited by 4 publications

References 95 publications

Three-Dimensional Dental Analysis for Sex Estimation in the Italian Population: A Pilot Study Based on a Geometric Morphometric and Artificial Neural Network Approach

Three-Dimensional Dental Analysis for Sex Estimation in the Italian Population: A Pilot Study Based on a Geometric Morphometric and Artificial Neural Network Approach

Three‐dimensional (3D) geometric morphometric analysis of human premolars to assess sexual dimorphism and biological ancestry in Australian populations

A Semi-Automatic Method on a Small Italian Sample for Estimating Sex Based on the Shape of the Crown of the Maxillary Posterior Teeth

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