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

James Bewes, Andrew Low, Anthony Morphett, F. Donald Pate, Maciej Henneberg

    Research output: Contribution to journalArticlepeer-review

    93 Citations (Scopus)

    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.

    Original languageEnglish
    Pages (from-to)40-43
    Number of pages4
    JournalJournal of Forensic and Legal Medicine
    Volume62
    DOIs
    Publication statusPublished - Feb 2019

    Keywords

    • Artificial intelligence
    • Artificial neural network
    • Deep learning
    • Sex determination
    • Skull determination

    Fingerprint

    Dive into the research topics of 'Artificial intelligence for sex classification of skeletal remains: Application of a deep learning neural network to human skulls: Application of a deep learning artificial neural network to human skulls'. Together they form a unique fingerprint.

    Cite this