Artificial intelligence (AI) is a broad, umbrella term that encompasses the theory and development of computer systems able to perform tasks normally requiring human intelligence. The aim of this study is to assess the radiology community’s attitude in Saudi Arabia toward the applications of AI. Methods: Data for this study were collected using electronic questionnaires in 2019 and 2020. The study included a total of 714 participants. Data analysis was performed using SPSS Statistics (version 25). Results: The majority of the participants (61.2%) had read or heard about the role of AI in radiology. We also found that radiologists had statistically different responses and tended to read more about AI compared to all other specialists. In addition, 82% of the participants thought that AI must be included in the curriculum of medical and allied health colleges, and 86% of the participants agreed that AI would be essential in the future. Even though human–machine interaction was considered to be one of the most important skills in the future, 89% of the participants thought that it would never replace radiologists. Conclusion: Because AI plays a vital role in radiology, it is important to ensure that radiologists and radiographers have at least a minimum understanding of the technology. Our finding shows an acceptable level of knowledge regarding AI technology and that AI applications should be included in the curriculum of the medical and health sciences colleges.

Acute appendicitis it a quite common abdominal disorder and considered as a difficult diagnosis. An accurate diagnosis is essential to prevent any complication from delayed surgical intervention. Aim: To evaluate the diagnostic accuracy of ultrasound in acute appendicitis cases in Saudi Arabia compared with histopathology. Moreover, to determine whether there is a correlation between the accuracy of ultrasound in acute appendicitis and the sonographers’ expertise. Methods: A retrospective study was conducted, including patients who admitted to the emergency room with clinical symptoms of suspected acute appendicitis and underwent ultrasound examinations. Diagnostic features, including diameter of the appendix ≥7 mm, free fluid, lack of compressibility, no appendix seen, normal appearance, and thick wall, were recorded for each patient. Results: Only 61 of the 132 patients in the study were accurately diagnosed with the use of ultrasound. Just 44 of them were diagnosed with appendicitis (true positives) and 17 without appendicitis (true negatives). However, 69 patients who had positive histopathologic results received a negative ultrasound diagnosis (false negatives), and 2 patients with negative histopathologic findings had a positive ultrasound diagnosis (false positives). There was no significant association between the accuracy of the ultrasound diagnosis and the years of experience of the sonographers. Conclusion: a low level of diagnostic accuracy was demonstrated when utilizing ultrasound to diagnose cases of acute appendicitis. In addition, no association was found between the years of experience of the sonographer conducting the examination and the diagnosis of acute appendicitis.