Bahakeem Basem H, Alobaidi Sultan F, Alzahrani Amjad S, Alhasawi Roudin, Alzahrani Abdulkarem, Alqahtani Wed, Alhashmi Alamer Lujain, Bin Laswad Bassam M, Al Shanbari Nasser
Department of Medical Imaging, College of Medicine, Umm Al-Qura University, Makkah, SAU.
Department of Medicine and Surgery, College of Medicine, Umm Al-Qura University, Makkah, SAU.
Cureus. 2023 Apr 10;15(4):e37391. doi: 10.7759/cureus.37391. eCollection 2023 Apr.
Background Artificial intelligence (AI) is a broad spectrum of computer-executed operations that mimics the human intellect. It is expected to improve healthcare practice in general and radiology in particular by enhancing image acquisition, image analysis, and processing speed. Despite the rapid development of AI systems, successful application in radiology requires analysis of social factors such as the public's perspectives toward the technology. Objectives The current study aims to investigate the general population's perspectives on AI implementation in radiology in the Western region of Saudi Arabia. Methods A cross-sectional study was conducted from November 2022 and July 2023 utilizing a self-administrative online survey distributed via social media platforms. A convenience sampling technique was used to recruit the study participants. After obtaining Institutional Review Board approval, data were collected from citizens and residents of the western region of Saudi Arabia aged 18 years or older. Results A total of 1,024 participants were included in the present study, with the mean age of respondents being 29.6 ± 11.3. Of them, 49.9% (511) were men, and 50.1% (513) were women. The comprehensive mean score of the first four domains among our participants was 3.93 out of 5.00. Higher mean scores suggest being more negative regarding AI in radiology, except for the fifth domain. Respondents had less trust in AI utilization in radiology, as evidenced by their overall distrust and accountability domain mean score of 3.52 out of 5. The majority of respondents agreed that it is essential to understand every step of the diagnostic process, and the mean score for the procedural knowledge domain was 4.34 out of 5. The mean score for the personal interaction domain was 4.31 out of 5, indicating that the participants agreed on the value of direct communication between the patient and the radiologist for discussing test results and asking questions. Our data show that people think AI is more effective than human doctors in making accurate diagnoses and decreasing patient wait times, with an overall mean score of the efficiency domain of 3.56 out of 5. Finally, the fifth domain, "being informed," had a mean score of 3.91 out of 5. Conclusion The application of AI in radiologic assessment and interpretation is generally viewed negatively. Even though people think AI is more efficient and accurate at diagnosing than humans, they still think that computers will never be able to match a specialist doctor's years of training.
背景 人工智能（AI）是一系列广泛的由计算机执行的操作，可模仿人类智能。人们期望它能通过提高图像采集、图像分析和处理速度，总体上改善医疗实践，尤其是放射学领域。尽管人工智能系统发展迅速，但在放射学中的成功应用需要分析社会因素，如公众对该技术的看法。
目的 本研究旨在调查沙特阿拉伯西部地区普通民众对放射学中人工智能应用的看法。
方法 2022年11月至2023年7月进行了一项横断面研究，采用通过社交媒体平台分发的自填式在线调查问卷。使用便利抽样技术招募研究参与者。获得机构审查委员会批准后，收集了沙特阿拉伯西部地区18岁及以上公民和居民的数据。
结果 本研究共纳入1024名参与者，受访者的平均年龄为29.6±11.3岁。其中，49.9%（511人）为男性，50.1%（513人）为女性。参与者前四个领域的综合平均得分为3.93（满分5.00）。除第五个领域外，较高的平均得分表明对放射学中人工智能的看法更负面。受访者对放射学中人工智能的使用信任度较低，其总体不信任和问责领域平均得分为3.52（满分5.00）。大多数受访者认为了解诊断过程的每一步很重要，程序知识领域的平均得分为4.34（满分5.00）。人际互动领域的平均得分为4.31（满分5.00），表明参与者认同患者与放射科医生直接沟通以讨论检查结果和提问的价值。我们的数据显示，人们认为人工智能在进行准确诊断和减少患者等待时间方面比人类医生更有效，效率领域的总体平均得分为3.56（满分5.00）。最后，第五个领域“被告知”的平均得分为3.91（满分5.00）。
结论 人工智能在放射学评估和解读中的应用总体上被负面看待。尽管人们认为人工智能在诊断方面比人类更高效、准确，但他们仍然认为计算机永远无法与专科医生多年的培训相媲美。
