Patients'Attitudes Toward the Use of Artificial Intelligence as aDiagnostic Tool in Radiology in Saudi Arabia:Cross-SectionalStudy

Background: Artificial intelligence (AI) is widely used in various medical fields, including diagnostic radiology as a tool forgreater efficiency, precision, and accuracy. The integration of AI as a radiological diagnostic tool has the potential to mitigatedelays in diagnosis, which could, in turn, impact patients'prognosis and treatment outcomes. The literature shows conflictingresults regarding patients'attitudes to AI as a diagnostic tool. To the best of our knowledge, no similar study has been conductedin Saudi Arabia. Objective: The objectives of this study are to examine patients'attitudes toward the use of AI as a tool in diagnostic radiologyat King Khalid University Hospital, Saudi Arabia. Additionally, we sought to explore potential associations between patients'attitudes and various sociodemographic factors. Methods: This descriptive-analytical cross-sectional study was conducted in a tertiary care hospital. Data were collected frompatients scheduled for radiological imaging through a validated self-administered questionnaire. The main outcome was to measurepatients'attitudes to the use of AI in radiology by calculating mean scores of 5 factors, distrust and accountability (factor 1),procedural knowledge (factor 2), personal interaction and communication (factor 3), efficiency (factor 4), and methods of providinginformation to patients (factor 5). Data were analyzed using the student ttest, one-way analysis of variance followed by post hocand multivariable analysis.Results: A total of 382 participants (n=273, 71.5% women and n=109, 28.5% men) completed the surveys and were includedin the analysis. The mean age of the respondents was 39.51 (SD 13.26) years. Participants favored physicians over AI for proceduralknowledge, personal interaction, and being informed. However, the participants demonstrated a neutral attitude for distrust andaccountability and for efficiency. Marital status was found to be associated with distrust and accountability, procedural knowledge,and personal interaction. Associations were also found between self-reported health status and being informed and between thefield of specialization and distrust and accountability. Conclusions: Patients were keen to understand the work of AI in radiology but favored personal interaction with a radiologist.Patients were impartial toward AI replacing radiologists and the efficiency of AI, which should be a consideration in future policydevelopment and integration. Future research involving multicenter studies in different regions of Saudi Arabia is required.