Impact of the rise of artificial intelligence in radiology: What do radiologists think?

Diagn Interv Imaging. 2019 Jun;100(6):327-336. doi: 10.1016/j.diii.2019.03.015. Epub 2019 May 6.


Purpose: The purpose of this study was to assess the perception, knowledge, wishes and expectations of a sample of French radiologists towards the rise of artificial intelligence (AI) in radiology.

Material and method: A general data protection regulation-compliant electronic survey was sent by e-mail to the 617 radiologists registered in the French departments of Nord and Pas-de-Calais (93 radiology residents and 524 senior radiologists), from both public and private institutions. The survey included 42 questions focusing on AI in radiology, and data were collected between January 16th and January 31st, 2019. The answers were analyzed together by a senior radiologist and a radiology resident.

Results: A total of 70 radiology residents and 200 senior radiologists participated to the survey, which corresponded to a response rate of 43.8% (270/617). One hundred ninety-eight radiologists (198/270; 73.3%) estimated they had received insufficient previous information on AI. Two hundred and fifty-five respondents (255/270; 94.4%) would consider attending a generic continuous medical education in this field and 187 (187/270; 69.3%) a technically advanced training on AI. Two hundred and fourteen respondents (214/270; 79.3%) thought that AI will have a positive impact on their future practice. The highest expectations were the lowering of imaging-related medical errors (219/270; 81%), followed by the lowering of the interpretation time of each examination (201/270; 74.4%) and the increase in the time spent with patients (141/270; 52.2%).

Conclusion: While respondents had the feeling of receiving insufficient previous information on AI, they are willing to improve their knowledge and technical skills on this field. They share an optimistic view and think that AI will have a positive impact on their future practice. A lower risk of imaging-related medical errors and an increase in the time spent with patients are among their main expectations.

Keywords: Artificial intelligence (AI); Machine learning; Radiologists; Survey.

MeSH terms

  • Adult
  • Aged
  • Artificial Intelligence*
  • Attitude of Health Personnel*
  • Female
  • France
  • Health Knowledge, Attitudes, Practice*
  • Humans
  • Male
  • Middle Aged
  • Radiology*
  • Self Report
  • Young Adult