AIMC Topic: Forensic Anthropology

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Sex estimation using sternum part lenghts by means of artificial neural networks.

Forensic science international
In addition to the pelvis, cranium and phalanges, the sternum is also used for postmortem sex identification. Bone measurements may be obtained on cadaveric bones. Alternatively, computerized tomography may be used to obtain measurements close to the...

SPINNE: An app for human vertebral height estimation based on artificial neural networks.

Forensic science international
The absence or poor preservation of vertebrae often prevent the application of the anatomical method for stature estimation. The main objective of this paper was to develop a web app based on artificial neural network (ANN) models to estimate the ver...

Artificial intelligence for sex determination of skeletal remains: Application of a deep learning artificial neural network to human skulls.

Journal of forensic and legal medicine
A deep learning artificial neural network was adapted to the task of sex determination of skeletal remains. The neural network was trained on images of 900 skulls virtually reconstructed from hospital CT scans. When tested on previously unseen images...

Sex Determination of 3D Skull Based on a Novel Unsupervised Learning Method.

Computational and mathematical methods in medicine
In law enforcement investigation cases, sex determination from skull morphology is one of the important steps in establishing the identity of an individual from unidentified human skeleton. To our knowledge, existing studies of sex determination of t...

Parzen neural networks: Fundamentals, properties, and an application to forensic anthropology.

Neural networks : the official journal of the International Neural Network Society
A novel, unsupervised nonparametric model of multivariate probability density functions (pdf) is introduced, namely the Parzen neural network (PNN). The PNN is intended to overcome the major limitations of traditional (either statistical or neural) p...

DXAGE: A New Method for Age at Death Estimation Based on Femoral Bone Mineral Density and Artificial Neural Networks.

Journal of forensic sciences
Age at death estimation in adult skeletons is hampered, among others, by the unremarkable correlation of bone estimators with chronological age, implementation of inappropriate statistical techniques, observer error, and skeletal incompleteness or de...

Sex determination from the femur in Portuguese populations with classical and machine-learning classifiers.

Journal of forensic and legal medicine
The assessment of sex is of paramount importance in the establishment of the biological profile of a skeletal individual. Femoral relevance for sex estimation is indisputable, particularly when other exceedingly dimorphic skeletal regions are missing...

Classification of Porcine Cranial Fracture Patterns Using a Fracture Printing Interface.

Journal of forensic sciences
Distinguishing between accidental and abusive head trauma in children can be difficult, as there is a lack of baseline data for pediatric cranial fracture patterns. A porcine head model has recently been developed and utilized in a series of studies ...

Use of pattern recognition and neural networks for non-metric sex diagnosis from lateral shape of calvarium: an innovative model for computer-aided diagnosis in forensic and physical anthropology.

International journal of legal medicine
Sex determination on skeletal remains is one of the most important diagnosis in forensic cases and in demographic studies on ancient populations. Our purpose is to realize an automatic operator-independent method to determine the sex from the bone sh...

An automatic method for skeletal patterns classification using craniomaxillary variables on a Colombian population.

Forensic science international
BACKGROUND: The mandibular bone is an important part of the forensic facial reconstruction and it has the possibility of getting lost in skeletonized remains; for this reason, it is necessary to facilitate the identification process simulating the ma...