Literature DB >> 33904953

Artificial intelligence in child abuse imaging.

James I Sorensen1, Rahul M Nikam2, Arabinda K Choudhary3.   

Abstract

There have been rapid advances in artificial intelligence (AI) technology in recent years, and the field of diagnostic imaging is no exception. Just as digital technology revolutionized how radiology is practiced, so these new technologies also appear poised to bring sweeping change. As AI tools make the transition from the theoretical to the everyday, important decisions need to be made about how they will be applied and what their role will be in the practice of radiology. Pediatric radiology presents distinct challenges and opportunities for the application of these tools, and in this article we discuss some of these, specifically as they relate to the prediction, identification and investigation of child abuse.

Entities:  

Keywords:  Artificial intelligence; Child abuse; Children; Machine learning; Radiology

Year:  2021        PMID: 33904953     DOI: 10.1007/s00247-021-05073-0

Source DB:  PubMed          Journal:  Pediatr Radiol        ISSN: 0301-0449


  2 in total

1.  European Society of Paediatric Radiology Artificial Intelligence taskforce: a new taskforce for the digital age.

Authors:  Lene Bjerke Laborie; Jaishree Naidoo; Erika Pace; Pierluigi Ciet; Christine Eade; Matthias W Wagner; Thierry A G M Huisman; Susan C Shelmerdine
Journal:  Pediatr Radiol       Date:  2022-06-22

2.  Artificial intelligence for radiological paediatric fracture assessment: a systematic review.

Authors:  Susan C Shelmerdine; Richard D White; Hantao Liu; Owen J Arthurs; Neil J Sebire
Journal:  Insights Imaging       Date:  2022-06-03
  2 in total

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