Age prediction formulae from radiographic assessment of skeletal maturation at the knee in an Irish population

O’Connor, Jean E.; Jt, Coyle; Bogue, Conor O.; Spence, Liam D.; Last, Jason

doi:10.1016/j.forsciint.2013.10.032

Cited by 33 publications

(27 citation statements)

References 29 publications

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“…These results are consistent with literature in humans and other animals showing that sexual maturity occurs prior to complete skeletal maturity (Lai et al 2008;O'Connor et al 2014;Kilborn, Trudel, and Uhthoff 2002;Cameron 2015;Porcu et al 1994). …”

Section: Sexual and Skeletal Assessments Of Maturity Confirmed That Ssupporting

confidence: 92%

Maturity-related Variability of the Thymus in Cynomolgus Monkeys (Macaca fascicularis)

et al. 2016

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Terminal body weights (TBWs), thymus weight parameters, and thymus morphology were retrospectively evaluated in 453 cynomolgus monkeys assigned to control groups on nonclinical toxicity studies. Morphology of bone, ovary, and testis/epididymis were used to determine maturity status of individual animals. There was no correlation between TBW and thymus weight (absolute and/or relative to TBW or brain weight). Thymus weight parameters and grades of decreased lymphocytes in the thymus were highly variable in immature animals compared to mature animals. There was also high (up to 11-fold) variability of thymus weight parameters within a given control group on the same study (generally 3 or 4 animals per sex). Several parameters evaluated had more pronounced age-related changes in males when compared to females. Our results demonstrate the inherent variability of thymus weight parameters and morphologic observations for cynomolgus monkeys on toxicology studies. Changes in thymus parameters in cynomolgus monkeys are unreliable indicators of immunomodulation or immunotoxicity in the absence of other relevant findings. Therefore, the thymus parameters commonly evaluated in preclinical safety assessments should not be the primary data set used to determine the presence of a direct test article-related effect on the immune system.

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Section: Sexual and Skeletal Assessments Of Maturity Confirmed That Ssupporting

confidence: 92%

Maturity-related Variability of the Thymus in Cynomolgus Monkeys (Macaca fascicularis)

et al. 2016

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“…The usefulness of many skeletal elements in the context of forensic age estimation has been extensively researched (e.g. Franklin and Flavel 2014;Lottering et al 2013;O'Connor et al 2014;Villa et al 2013;Wittschieber et al 2013a)). Sub-adult age estimation methodologies commonly employed are based on the analysis of characteristics of dental and/or skeletal development (AlQahtani et al 2010;Demirjian and Goldstein 1976;Demirjian et al 1973;Fanning 1961;Moorrees et al 1963a;Moorrees et al 1963b;Schour and Massler 1941).…”

Section: 1mentioning

confidence: 99%

Age estimation in a sub-adult Western Australian population based on the analysis of the pelvic girdle and proximal femur

Sullivan

Flavel

Franklin

2017

Forensic Science International

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“…Therefore, it will be a waste of money and time. There are many reported methods that used bones for age estimation and they are subdivided into three main categories: image processing [29][30][31], by comparing with bone age atlas [32][33][34], and statistical regression analysis [35][36][37][38]. As being compared with the atlas, as the name proposes, X-ray image of the subjects are being made comparison with an atlas which contains a set of radiographs of identified gender and age.…”

Section: Results and Analysismentioning

confidence: 99%

Random forest age estimation model based on length of left hand bone for Asian population

Darmawan¹,

Abidin²,

Kasim³

et al. 2020

IJECE

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In forensic anthropology, age estimation is used to ease the process of identifying the age of a living being or the body of a deceased person. Nonetheless, the specialty of the estimation models is solely suitable to a specific people. Commonly, the models are inter and intra-observer variability as the qualitative set of data is being used which results the estimation of age to rely on forensic experts. This study proposes an age estimation model by using length of bone in left hand of Asian subjects range from newborn up to 18-year-old. One soft computing model, which is Random Forest (RF) is used to develop the estimation model and the results are compared with Artificial Neural Network (ANN) and Support Vector Machine (SVM), developed in the previous case studies. The performance measurement used in this study and the previous case study are R-square and Mean Square Error (MSE) value. Based on the results produced, the RF model shows comparable results with the ANN and SVM model. For male subjects, the performance of the RF model is better than ANN, however less ideal than SVM model. As for female subjects, the RF model overperfoms both ANN and SVM model. Overall, the RF model is the most suitable model in estimating age for female subjects compared to ANN and SVM model, however for male subjects, RF model is the second best model compared to the both models. Yet, the application of this model is restricted only to experimental purpose or forensic practice.

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Age prediction formulae from radiographic assessment of skeletal maturation at the knee in an Irish population

Cited by 33 publications

References 29 publications

Maturity-related Variability of the Thymus in Cynomolgus Monkeys (Macaca fascicularis)

Maturity-related Variability of the Thymus in Cynomolgus Monkeys (Macaca fascicularis)

Age estimation in a sub-adult Western Australian population based on the analysis of the pelvic girdle and proximal femur

Random forest age estimation model based on length of left hand bone for Asian population

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