Evaluating the impact of AI assistance on decision-making in emergency doctors interpreting chest X-rays: a multi-reader multi-case study
Improvements in diagnosis and patient management without meaningful increases in interpretation time suggest AI assistance could benefit clinical decisions involving chest X-ray interpretation. Further studies are required to ascertain if such improvements translate to improved patient care.
Authors
- Mark Gillett (ORCID: https://orcid.org/0000-0002-6287-7137)
- Michael Dinh (ORCID: https://orcid.org/0000-0002-0086-455X)
- Radhika V. Seimon (ORCID: https://orcid.org/0000-0002-3903-4801)
- Farah Magrabi (ORCID: https://orcid.org/0000-0002-8426-5588)
- Emily Symes (ORCID: https://orcid.org/0000-0001-7928-4541)
- David Lyell (ORCID: https://orcid.org/0000-0002-2695-0368)
- Anindya Pradipta Susanto (ORCID: https://orcid.org/0000-0001-5155-6904)
- Enrico Coiera (ORCID: https://orcid.org/0000-0002-6444-6584)
- Bashir Antoine Chakar (ORCID: https://orcid.org/0009-0000-0571-5222)
- Ned Abraham
Institutions
- Royal Prince Alfred Hospital (AU)
- Royal North Shore Hospital (AU)
- Canterbury Hospital (AU)
- Universitas 17 Agustus 1945 Jakarta (ID)
- Sydney Local Health District (AU)
- Macquarie University (AU)
Publication Details
- Journal
- Emergency Medicine Journal
- Published
- 2025-10-13
- DOI
- https://doi.org/10.1136/emermed-2024-214781
- Citations
- 1
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 0.65
Funders
- Australian Government
- NSW Agency for Clinical Innovation