Rawashdeh Mohammad A, Almazrouei Sara, Zaitoun Maha, Kumar Praveen, Saade Charbel
Faculty of Health Sciences, Gulf Medical University, Ajman, UAE.
Faculty of Applied Medical Sciences, Jordan University of Science and Technology, Irbid 222110, Jordan.
Int J Biomed Imaging. 2024 Mar 8;2024:7001343. doi: 10.1155/2024/7001343. eCollection 2024.
Artificial intelligence (AI) applications are rapidly advancing in the field of medical imaging. This study is aimed at investigating the perception and knowledge of radiographers towards artificial intelligence.
An online survey employing Google Forms consisting of 20 questions regarding the radiographers' perception of AI. The questionnaire was divided into two parts. The first part consisted of demographic information as well as whether the participants think AI should be part of medical training, their previous knowledge of the technologies used in AI, and whether they prefer to receive training on AI. The second part of the questionnaire consisted of two fields. The first one consisted of 16 questions regarding radiographers' perception of AI applications in radiology. Descriptive analysis and logistic regression analysis were used to evaluate the effect of gender on the items of the questionnaire.
Familiarity with AI was low, with only 52 out of 100 respondents (52%) reporting good familiarity with AI. Many participants considered AI useful in the medical field (74%). The findings of the study demonstrate that nearly most of the participants (98%) believed that AI should be integrated into university education, with 87% of the respondents preferring to receive training on AI, with some already having prior knowledge of AI used in technologies. The logistic regression analysis indicated a significant association between male gender and experience within the range of 23-27 years with the degree of familiarity with AI technology, exhibiting respective odds ratios of 1.89 (COR = 1.89) and 1.87 (COR = 1.87).
This study suggests that medical practices have a favorable attitude towards AI in the radiology field. Most participants surveyed believed that AI should be part of radiography education. AI training programs for undergraduate and postgraduate radiographers may be necessary to prepare them for AI tools in radiology development.
人工智能（AI）应用在医学成像领域正迅速发展。本研究旨在调查放射技师对人工智能的认知和了解。
采用谷歌表单进行在线调查，包含20个关于放射技师对人工智能认知的问题。问卷分为两部分。第一部分包括人口统计学信息，以及参与者是否认为人工智能应成为医学培训的一部分、他们之前对人工智能所使用技术的了解，以及他们是否希望接受人工智能培训。问卷的第二部分由两个领域组成。第一个领域包括16个关于放射技师对放射学中人工智能应用认知的问题。采用描述性分析和逻辑回归分析来评估性别对问卷各项的影响。
对人工智能的熟悉程度较低，100名受访者中只有52人（52%）表示对人工智能非常熟悉。许多参与者认为人工智能在医学领域有用（74%）。研究结果表明，几乎大多数参与者（98%）认为人工智能应融入大学教育，87%的受访者希望接受人工智能培训，其中一些人已经对人工智能所使用的技术有一定了解。逻辑回归分析表明，男性性别以及23至27年的工作经验与对人工智能技术的熟悉程度之间存在显著关联，各自的优势比分别为1.89（COR = 1.89）和1.87（COR = 1.87）。
本研究表明，医疗实践对放射学领域的人工智能持积极态度。大多数接受调查的参与者认为人工智能应成为放射学教育的一部分。可能有必要为本科和研究生放射技师开展人工智能培训项目，以使他们为放射学发展中的人工智能工具做好准备。
