BoekenTFeydyJLeclerASoyerPFeydyABaratM, et al.Artificial intelligence in diagnostic and interventional radiology: Where are we now?Diagn Interv Imaging. 2023;104(1):1-5. doi: 10.1016/j.diii.2022.11.004
2.
SoyerPFishmanEKRoweSPPatlasMNChassagnonG. Does artificial intelligence surpass the radiologist?Diagn Interv Imaging. 2022;103(10):445-447. doi: 10.1016/j.diii.2022.08.001
3.
WigginsWFTejaniAS. On the opportunities and risks of foundation models for natural language processing in radiology. Radiol Artif Intell. 2022;4(4): e220119. doi: 10.1148/ryai.220119
4.
FerresJMLWeeksWBChuLCRoweSPFishmanEK. Beyond chatting: The opportunities and challenges of ChatGPT in medicine and radiology. Diagn Interv Imaging. 2023. doi:10.1016/j.diii.2023.02.006
5.
LeclerADuronLSoyerP. Revolutionizing radiology with GPT-based models: Current applications, future possibilities and limitations of ChatGPT. Diagn Interv Imaging. 2023. doi:10.1016/j.diii.2023.02.003
6.
TanguayWAcarPFineBAbdolellMGongBCadrin-ChênevertA, et al. Assessment of radiology artificial intelligence software: A validation and evaluation framework. Can Assoc Radiol J2022;74(2):326-333. doi:10.1177/08465371221135760.