Sex determination using discriminant analysis of upper and lower extremity bones: New approach using the volume and surface area of digital model

Lee, U-Young; Kim, In‐Beom; Kwak, Dai-Soon

doi:10.1016/j.forsciint.2015.05.017

Cited by 22 publications

(18 citation statements)

References 20 publications

(25 reference statements)

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“…Using landmark methodology and proximal tibial data, sex has been diagnosed with a high degree of accuracy (87.5%–91.80% after C-V) when size and shape are combined [7]. Even though sex determination based on whole 3D models is often accurate enough [57], the surface-based techniques applied in this study (with success rates of 76.79%–85.25% for shape–size and 60.66%–71.58% for shape data) proved to be less successful than landmark methods. The accuracy of prediction achieved a level considered acceptable only in general osteological, but not forensic, contexts [58].…”

Section: Discussionmentioning

confidence: 99%

Sexual Dimorphism of the Human Tibia through Time: Insights into Shape Variation Using a Surface-Based Approach

et al. 2016

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In this paper we present a three-dimensional (3D) morphometrical assessment of human tibia sexual dimorphism based on whole bone digital representation. To detect shape–size and shape differences between sexes, we used geometric morphometric tools and colour-coded surface deviation maps. The surface-based methodology enabled analysis of sexually dimorphic features throughout the shaft and articular ends of the tibia. The overall study dataset consisted of 183 3D models of adult tibiae from three Czech population subsets, dating to the early medieval (9–10th century) (N = 65), early 20th century (N = 61) and 21st-century (N = 57). The time gap between the chronologically most distant and contemporary datasets was more than 1200 years. The results showed that, in all three datasets, sexual dimorphism was pronounced. There were some sex-dimorphic characteristics common to all three samples, such as tuberosity protrusion, anteriorly bowed shaft and relatively larger articular ends in males. Diachronic comparisons also revealed substantial shape variation related to the most dimorphic area. Male/female distinctions showed a consistent temporal trend regarding the location of dimorphic areas (shifting distally with time), while the maximal deviation between male and female digitized surfaces fluctuated and reached the lowest level in the 21st-century sample. Sex determination on a whole-surface basis yielded the lowest return of correct sex assignment in the 20th-century group, which represented the lowest socioeconomic status. The temporal variation could be attributed to changes in living conditions, the decreasing lower limb loading/labour division in the last 12 centuries having the greatest effect. Overall, the results showed that a surface-based approach is successful for analysing complex long bone geometry.

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Section: Discussionmentioning

confidence: 99%

Sexual Dimorphism of the Human Tibia through Time: Insights into Shape Variation Using a Surface-Based Approach

et al. 2016

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“…These ratios were subjected to stepwise discriminant analysis to select the appropriate ratios for creating an effective equation for assignment of sex. The accuracy rates of the equation were tested by 'leave-one-out' classification to evaluate the capacity of the equation to estimate sex (Ogawa et al, 2013;Alunni et al, 2015;Lee et al, 2015). The average values of each ratio obtained from individual measurements were calculated by the equation.…”

Section: Statistical Analysis and Sex-determining Bone Morphology Equmentioning

confidence: 99%

Gender-Related Differences in Pelvic Morphometrics of the Retriever Dog Breed

Nganvongpanit

Pitakarnnop

Buddhachat

et al. 2016

Anat. Histol. Embryol.

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This study presents the results from a morphometric analysis of 52 dry Retriever dog pelvic bones (30 male, 22 female). A total of 20 parameters were measured using an osteometric board and digital vernier caliper. Six parameters were found to be significantly higher (P < 0.05) in males than in females, while one parameter was significantly higher (P < 0.05) in females than in males. However, none of the measured parameters demonstrated clear cut-off values with no intersect between males and females. Therefore, we generated a stepwise discriminant analysis from all 20 parameters in order to develop a possible working equation to discriminate gender from a dog pelvic bone. Stepwise discriminant analysis was used to create a discrimination function: Y = [82.1*PS/AII] - [50.72*LIS/LI] - [23.09*OTD/SP] + [7.69*SP/IE] + [6.52*IC/OW] + [7.67*ISA/OW] + [20.77*AII/PS] + [504.71*OW/ISA] - [90.84*PS/ISA] - [148.95], which showed an accuracy rate of 86.27%. This is the first study presenting an equation/function for use in discriminating gender from a dog's pelvic measurements. The results can be used in veterinary forensic anthropology and also show that a dog's pelvis presents sexual dimorphisms, as in humans.

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“…In the literature, there are some examples of the use of discriminant analysis in anatomy (Alunni et al, 2015;Lee et al, 2015). In the article by Alunni et al (2015), the authors show how to use the femoral bones to determine gender.…”

Section: Application Of Discriminant Analysis In Medical Sciencementioning

confidence: 99%

“…In the article by Alunni et al (2015), the authors show how to use the femoral bones to determine gender. In the second cited article by Lee et al (2015), information is presented regarding how volume and surface area of different bone types were used to the same aim.…”

Section: Application Of Discriminant Analysis In Medical Sciencementioning

confidence: 99%

Significance of Discriminant Analysis in Prediction of Pregnancy in IVF Treatment

Milewska

Jankowska

Cwalina

et al. 2015

Studies in Logic, Grammar and Rhetoric

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Many factors play an important role in prediction of infertility treatment outcome (for example, female age and quality of oocytes or embryos are the most important prognostic factors concerning positive IVF outcome). The purpose of this study was to identify a set of variables that could fulfill criteria for prediction of pregnancy in IVF patients through the application of data mining -using the discriminant analysis method. The principle of this method is to establish a set of rules that allows one to place multi-dimensional objects into one of two analyzed groups (pregnant or not pregnant). Six hundred and ten IVF cycles were included in the analysis and the following variables were taken into consideration: female age, number and quality of retrieved oocytes, number and quality of embryos, number of transferred embryos, and outcome of treatment. Discriminant analysis allowed for the creation of a model with a 51.22% correctness of prediction to achieve pregnancy during IVF treatment and with 74.07% correctly predicted failure of pregnancy. Therefore, the created model is more suitable for the prediction of a negative outcome (lack of pregnancy) during IVF treatment and offers an option for adjustments to be made during infertility treatment.

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Sex determination using discriminant analysis of upper and lower extremity bones: New approach using the volume and surface area of digital model

Cited by 22 publications

References 20 publications

Sexual Dimorphism of the Human Tibia through Time: Insights into Shape Variation Using a Surface-Based Approach

Sexual Dimorphism of the Human Tibia through Time: Insights into Shape Variation Using a Surface-Based Approach

Gender-Related Differences in Pelvic Morphometrics of the Retriever Dog Breed

Significance of Discriminant Analysis in Prediction of Pregnancy in IVF Treatment

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