Knowledge And Perception Of The Use Of Artificial Intelligence And Its Implementation In The Radiology Field

Abstract

Background: The rise of artificial intelligence (AI) in medicine, and particularly in radiology, is becoming increasingly prominent. Its impact will transform the way the specialty is practiced and the current and future education model. AI has been developing for decades, but in recent years its use in the field of health care has experienced an exponential increase. Currently, there is little doubt that these tools have transformed clinical practice. Therefore, it is vital to identify how the population perceives its implementation to be able to recommend strategies for acceptance and implementation and to improve or prevent problems arising from future applications. This study aims to describe the population’s perception and knowledge of the use of AI as a health support tool and its application to radiology through a validated questionnaire, in order to develop strategies aimed at increasing acceptance of AI use, reducing possible resistance to change and identifying possible socio-demographic factors related to perception and knowledge. Methods: A cross-sectional observational study was conducted using an anonymous and voluntarily validated questionnaire aimed at the population of KSA aged 18 years or older. The survey addresses 4 dimensions defined to describe users’ perception of the use of AI in radiology, (1) “distrust and accountability,” (2) “personal interaction,” (3) “efficiency,” and (4) “being informed,” all with questions in a Likert scale format. Results closer to 5 refer to a negative perception of the use of AI, while results closer to 1 express a positive perception. Univariate and bivariate analyses were performed to assess possible associations between the 4 dimensions and socio-demographic characteristics. Results: A total of 379 users responded to the survey, with an average age of 43.9 (SD 17.52) years and 59.8% (n=226) of them identified as female. In addition, 89.8% (n=335) of respondents indicated that they understood the concept of AI. Of the 4 dimensions analyzed, “distrust and accountability” obtained a mean score of 3.37 (SD 0.53), “personal interaction” obtained a mean score of 4.37 ([1]SD 0.60), “efficiency” obtained a mean score of 3.06 (SD 0.73) and “being informed” obtained a mean score of 3.67 (SD 0.57). Conclusions: The majority of the sample investigated reported being familiar with the concept of AI, with varying degrees of acceptance of its implementation in radiology. It is clear that the most conflictive dimension is “personal interaction,” whereas “efficiency” is where there is the greatest acceptance, being the dimension in which there are the best expectations for the implementation of AI in radiology.