Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
Editorial
. 2024 Feb;34(2):808-809.
doi: 10.1007/s00330-023-10240-y. Epub 2023 Sep 22.

Ready for testing artificial intelligence in radiology clinical practice: We would do well to be in the front line leveraging their strengths but also highlighting today weaknesses

Benjamin Bender  1
Affiliations
Editorial

Ready for testing artificial intelligence in radiology clinical practice: We would do well to be in the front line leveraging their strengths but also highlighting today weaknesses

Benjamin Bender. Eur Radiol. 2024 Feb.
No abstract available

PubMed Disclaimer

Conflict of interest statement

The author of this manuscript is co-founder, shareholder, and CTO of AIRAmed GmbH.

Comment on

  • Effects of a comprehensive brain computed tomography deep learning model on radiologist detection accuracy.
    Buchlak QD, Tang CHM, Seah JCY, Johnson A, Holt X, Bottrell GM, Wardman JB, Samarasinghe G, Dos Santos Pinheiro L, Xia H, Ahmad HK, Pham H, Chiang JI, Ektas N, Milne MR, Chiu CHY, Hachey B, Ryan MK, Johnston BP, Esmaili N, Bennett C, Goldschlager T, Hall J, Vo DT, Oakden-Rayner L, Leveque JC, Farrokhi F, Abramson RG, Jones CM, Edelstein S, Brotchie P. Buchlak QD, et al. Eur Radiol. 2024 Feb;34(2):810-822. doi: 10.1007/s00330-023-10074-8. Epub 2023 Aug 22. Eur Radiol. 2024. PMID: 37606663 Free PMC article.

References

    1. Alexander R, Waite S, Bruno MA et al (2022) Mandating limits on workload, duty, and speed in radiology. Radiology 304(2):274–282. 10.1148/radiol.212631 - PMC - PubMed
    1. Muroff LR, Berlin L. Speed versus interpretation accuracy: current thoughts and literature review. AJR Am J Roentgenol. 2019;213(3):490–492. doi: 10.2214/AJR.19.21290. - DOI - PubMed
    1. Miles CR, Lehman CD. Artificial intelligence for image interpretation: point – the radiologist’s potential friend. AJR Am J Roentgenol. 2021;217:556–557. doi: 10.2214/AJR.21.25564. - DOI - PubMed
    1. Lexa FJ, Jha S. Artificial intelligence for image interpretation: counterpoint – the radiologist’s incremental foe. AJR Am J Roentgenol. 2021;217:558–559. doi: 10.2214/AJR.21.25484. - DOI - PubMed
    1. Buchlak QD, Tang CHM, Seah JCY, et al. Effects of a comprehensive brain computed tomography deep learning model on radiologist detection accuracy. Eur Radiol. 2023 doi: 10.1007/s00330-023-10074-8. - DOI - PMC - PubMed

LinkOut - more resources