Real-life benefit of artificial intelligence-based fracture detection in a pediatric emergency department
Question Does an artificial intelligence-based software for fracture detection influence inexperienced physicians in a real-life pediatric trauma population? Findings Addition of a well-performing artificial intelligence-based software led to a limited increase in diagnostic accuracy of inexperienced human readers. Clinical relevance Diagnosing fractures in children is especially challenging for less experienced physicians. High-performing artificial intelligence-based software as a "second set of eyes," enhances diagnostic accuracy in a common pediatric emergency room setting.
Authors
- Martin Lacher (ORCID: https://orcid.org/0000-0002-4616-9464)
- Maciej Rosołowski (ORCID: https://orcid.org/0000-0003-3204-748X)
- Daniel Gräfe (ORCID: https://orcid.org/0000-0002-7680-0990)
- W. Hirsch (ORCID: https://orcid.org/0000-0003-0960-3740)
- J Pape (ORCID: https://orcid.org/0009-0002-1280-3866)
- Annika Brandau (ORCID: https://orcid.org/0000-0003-2947-7809)
- Steffi Mayer
- Maria Ziegner
- Tibor Kelety
Institutions
- University Hospital Leipzig (DE)
- Leipzig University (DE)
Publication Details
- Journal
- European Radiology
- Published
- 2025-04-07
- DOI
- https://doi.org/10.1007/s00330-025-11554-9
- Citations
- 14
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 9.16