title: A comparison between neural network and other metric methods to determine sex from the upper femur in a modern French population.
abstract: Forensic anthropologists are frequently asked to assess partial or badly damaged skeletal remains. One such request led us to compare the predictive accuracy of different mathematical methods using four non-standard measurements of the proximal femur (trochanter-diaphysis distance (TD), greater-lesser trochanter distance (TT), greater trochanter width (TW) and trochanter-head distance (TH)). These measurements were taken on 76 femurs (38 males and 38 females) of French individuals. Intra- and inter-observer trials did not reveal any significant statistical differences. The predictive accuracy of three models built using linear and non-linear modelling techniques was compared: discriminant analysis, logistic regression and neural network. The neural network outperformed discriminant analysis and, to a lesser extent, logistic regression. Indeed, the best results were obtained with a neural network that correctly classified 93.4% of femurs, with similar results in males (92.1%) and females (94.7%). Univariate functions were less accurate (68-88%). Discriminant analysis and logistic regression, both using all four variables, led to slightly better results (88.2% and 89.5%, respectively). In addition, all the models, save the neural network, led to unbalanced results between males and females. In conclusion, the artificial neural network is a powerful classification technique that may improve the accuracy rate of sex determination models for skeletal remains.
authors.affiliation: Edhec Business School, 400 Promenade des Anglais, Nice, France.
authors.forename: Ph
authors.initials: P
authors.lastname: du Jardin
authors.forename: J
authors.initials: J
authors.lastname: Ponsaillé
authors.forename: V
authors.initials: V
authors.lastname: Alunni-Perret
authors.forename: G
authors.initials: G
authors.lastname: Quatrehomme
mesh_terms: D000369:Aged, 80 and over; D016002:Discriminant Analysis; D005260:Female; D005269:Femur / Q000033:anatomy & histology*; D018732:Forensic Anthropology / Q000379:methods; D005602:France; D006801:Humans; D016015:Logistic Models; D008297:Male; D016571:Neural Networks, Computer; D054881:Sex Determination by Skeleton / Q000379:methods*