• Efficiency: Efficiency was assessed based on the duration of scans, with patients expecting AI to shorten the amount of time necessary for full assessments, enabling them to be assisted sooner and at lower costs.

• Personal Interaction: Patients unambiguously expressed the desire for personal interactions with doctors when receiving exam results, as it enables them to safely ask questions and allows them to understand their results and their reliability. They believe human dialogue is important in such matters.


• Accountability: Patients question who is responsible for errors made by computers, with some saying humans will always be responsible because computers are just “giant calculators” or “dead things”.

Despite their skepticism and lack of knowledge on the use of AI, most feel that it is a development that will eventually take root in healthcare and other industries, though not in the near future.

The findings illustrate the need for clear communication among patients, referring physicians and radiologists on how AI is implemented in diagnostic radiology procedures, including scan acquisition, scan evaluation and the sharing of results. Haan, however, cautions that more quantitative analyses are required to validate the findings of this study.

“We are in the process of writing another article on this topic in which we aim at validating a patient survey on AI in radiology. Before developing and implementing an AI system for a particular radiological task, it would be very useful to perform a patient survey, since patient preferences determine the boundaries within which an AI system should function. The aim of our new study is therefore to develop and validate a standardized patient questionnaire on the use of AI in radiology using the six domains of our qualitative study. The data are already collected among patients and we are now analyzing them.”

The findings were published in the Journal of the American College of Radiology.

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