Medical Diagnostic Imaging Department, College of Health Sciences, University of Sharjah, Sharjah, UAE.
Medical Diagnostic Imaging Department, College of Health Sciences, University of Sharjah, Sharjah, UAE.
Acad Radiol. 2022 Jan;29(1):87-94. doi: 10.1016/j.acra.2020.09.014. Epub 2020 Oct 29.
This study aimed to investigate radiologists' and radiographers' knowledge, perception, readiness, and challenges regarding Artificial Intelligence (AI) integration into radiology practice.
An electronically distributed cross-sectional study was conducted among radiologists and radiographers in the United Arab Emirates. The questionnaire captured the participants' demographics, qualifications, professional experience, and postgraduate training. Their knowledge, perception, organisational readiness, and challenges regarding AI integration into radiology were examined.
There was a significant lack of knowledge and appreciation of the integration of AI into radiology practice. Organisations are stepping toward building AI implementation strategies. The availability of appropriate training courses is the main challenge for both radiographers and radiologists.
The excitement of AI implementation into radiology practise was accompanied by a lack of knowledge and effort required to improve the user's appreciation of AI. The knowledge gap requires collaboration between educational institutes and professional bodies to develop structured training programs for radiologists and radiographers.
本研究旨在调查放射科医生和放射技师在人工智能（AI）融入放射科实践方面的知识、认知、准备情况和面临的挑战。
在阿拉伯联合酋长国，对放射科医生和放射技师进行了一项电子分布式横断面研究。调查问卷收集了参与者的人口统计学、资格、专业经验和研究生培训信息。研究调查了他们在 AI 融入放射科方面的知识、认知、组织准备情况和面临的挑战。
研究发现，放射科医生和放射技师对将 AI 融入放射科实践的知识和认识明显不足。各组织正在着手制定 AI 实施策略。对于放射技师和放射科医生来说，缺乏合适的培训课程是主要挑战。
将 AI 应用于放射科实践的热情伴随着提高用户对 AI 认识所需的知识和努力的缺乏。知识差距需要教育机构和专业机构之间的合作，为放射科医生和放射技师制定结构化的培训计划。
