斯里兰卡放射学本科生对人工智能用于医学成像的态度

N. Chandrasiri, Amila Abeyweera, B. Weerakoon
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引用次数: 0

摘要

本研究旨在评估斯里兰卡放射学本科生对人工智能(AI)用于医学成像的态度。采用谷歌表格调查管理软件设计的电子问卷进行数据收集。问卷由不同的部分组成,以评估参与者的人口统计状况、对医学影像人工智能的态度、实践和知识。共有168名学生回答了问卷。其中以女性居多(64.3%)。大多数受访者(92.3%)表示他们在临床培训期间曾实践过x线平片成像方式。约67.9%的受访者知道医学成像中使用的基于人工智能的应用程序。然而,大多数受访者(51.17%)认为,在可预见的未来,人工智能将彻底改变和革新医学成像工具和方法。大多数受访者(64.29%)认为,基于人工智能的应用程序的使用将使放射技师的职责在未来5-10年内更具技术性。超过三分之二的受访者(73.8%)表示他们有兴趣参与任何基于人工智能技术的研究。在亚组分析中,男、女受访者的态度差异有统计学意义(p<0.05),而不同学年的态度差异无统计学意义(p<0.05)。总而言之,受访者对人工智能表现出良好的态度,人工智能彻底改变了医学成像,使放射技师的工作更具技术性。这导致了将人工智能技术纳入本科和研究生培训的强烈需求。因此,在医学影像领域对放射学本科学生进行这些新兴技术的教育以及如何有效地使用这些技术是至关重要的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Attitude of Sri Lankan radiography undergraduates towards artificial intelligence used in medical imaging
This study was conducted to evaluate the attitude of radiography un-dergraduates in Sri Lanka towards artificial intelligence (AI) on medical imaging. An electronic questionnaire designed by Google forms survey administration software was used for data collection. The questionnaire consisted of different sections to evaluate demographic status of the participants, attitude, practice and knowledge related to AI on medical imaging. A total of 168 students responded to the questionnaire. The majority of them (64.3%) were female. Most of the respondents (92.3%) stated that they have practiced plain radiography imaging mo-dality during their clinical training. Around 67.9% respondents were aware about the AI based applications used in medical imaging. How-ever, the majority of respondents (51.17%) opined that AI will drastical-ly change and revolutionize medical imaging tools and methods in a foreseeable future. Most of the respondents (64.29%) believed that the use of AI based applications will make a radiographer’s duties more technical in the next 5-10 years. More than two thirds of the respond-ents (73.8%) stated their interest to involve any research on AI based techniques. In sub group analysis, there is a significant difference (p>0.05) of attitude between male and female respondents while no significant difference (p<0.05) of attitude between academic years. In conclusion responders showed a favorable attitude on AI which revolu-tionize medical imaging making radiographers duties more technical. It led to a strong demand to include AI technologies in both undergradu-ate and postgraduate training. Therefore, it is essential to take the lead in educating radiography undergraduate students about these emerg-ing technologies in the field of medical imaging and how to work effi-ciently with those technologies.
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