Nordic radiographers’ and students’ perspectives on artificial intelligence – A cross-sectional online survey

Author:

Pedersen M.R.V.ORCID,Kusk M.W.ORCID,Lysdahlgaard S.ORCID,Mork-Knudsen H.ORCID,Malamateniou C.,Jensen J.ORCID

Publisher

Elsevier BV

Reference32 articles.

1. The impact of artificial intelligence on radiography as a profession: a narrative review;Al-Naser;J Med Imaging Radiat Sci,2023

2. Artificial intelligence-based prediction of cervical lymph node metastasis in papillary thyroid cancer with CT;Wang;Eur Radiol,2023

3. Clinical validation of an artificial intelligence model for detecting distal radius, ulnar styloid, and scaphoid fractures on conventional wrist radiographs;Lee;Diagnostics,2023

4. A deep learning algorithm for radiographic measurements of the hip in adults-a reliability and agreement study;Jensen;Diagnostics,2022

5. Minimal hip joint space width measured on X-rays by an artificial intelligence algorithm—a study of reliability and agreement;Andersen;BioMedInformatics,2023

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