Breitwieser, M.; Zirknitzer, S.; Poslusny, K.; Freude, T.; Scholsching, J.; Bodenschatz, K.; Wagner, A.; Hergan, K.; Schaffert, M.; Metzger, R.;
et al. AI in Fracture Detection: A Cross-Disciplinary Analysis of Physician Acceptance Using the UTAUT Model. Diagnostics 2025, 15, 2117.
https://doi.org/10.3390/diagnostics15162117
AMA Style
Breitwieser M, Zirknitzer S, Poslusny K, Freude T, Scholsching J, Bodenschatz K, Wagner A, Hergan K, Schaffert M, Metzger R,
et al. AI in Fracture Detection: A Cross-Disciplinary Analysis of Physician Acceptance Using the UTAUT Model. Diagnostics. 2025; 15(16):2117.
https://doi.org/10.3390/diagnostics15162117
Chicago/Turabian Style
Breitwieser, Martin, Stephan Zirknitzer, Karolina Poslusny, Thomas Freude, Julia Scholsching, Karl Bodenschatz, Anton Wagner, Klaus Hergan, Matthias Schaffert, Roman Metzger,
and et al. 2025. "AI in Fracture Detection: A Cross-Disciplinary Analysis of Physician Acceptance Using the UTAUT Model" Diagnostics 15, no. 16: 2117.
https://doi.org/10.3390/diagnostics15162117
APA Style
Breitwieser, M., Zirknitzer, S., Poslusny, K., Freude, T., Scholsching, J., Bodenschatz, K., Wagner, A., Hergan, K., Schaffert, M., Metzger, R., & Marko, P.
(2025). AI in Fracture Detection: A Cross-Disciplinary Analysis of Physician Acceptance Using the UTAUT Model. Diagnostics, 15(16), 2117.
https://doi.org/10.3390/diagnostics15162117
