ArticleInternational journal of legal medicine2017
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.
Article in International journal of legal medicine, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.
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Who cites it
4 citing papers in PubMed, 1 synthesis or guideline pooled it, 14 citations in OpenAlex.
- Artificial intelligence in forensic science: a systematic review. Part I: personal identification.International journal of legal medicine · 2026Pooled it
- Deep learning-based sex estimation from multi-planar cranial CT images in a Thai population.Anatomical science international · 2026Article
- Developing a fully applicable machine learning (ML) based sex classification model using linear cranial dimensions.Scientific reports · 2024Article
- DXAGE 2.0 - adult age at death estimation using bone loss in the proximal femur and the second metacarpal.International journal of legal medicine · 2022Article
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Authors and funding
3 authors at 2 institutions in 1 country.
Funding
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Abstract
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 shape and to test an intelligent, automatic pattern recognition system in an anthropological domain. Our multiple-classifier system is based exclusively on the morphological variants of a curve that represents the sagittal profile of the calvarium, modeled via artificial neural networks, and yields an accuracy higher than 80 %. The application of this system to other bone profiles is expected to further improve the sensibility of the methodology.
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