| Literature DB >> 30639854 |
James Bewes1, Andrew Low2, Antony Morphett3, F Donald Pate4, Maciej Henneberg5.
Abstract
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 of skulls, the artificial neural network showed 95% accuracy at sex determination. Artificial intelligence methods require no significant expertise to implement once trained, are rapid to use, and have the potential to eliminate human bias from sex estimation of skeletal remains.Entities:
Keywords: Artificial intelligence; Artificial neural network; Deep learning; Sex determination; Skull determination
Mesh:
Year: 2019 PMID: 30639854 DOI: 10.1016/j.jflm.2019.01.004
Source DB: PubMed Journal: J Forensic Leg Med ISSN: 1752-928X Impact factor: 1.614