评估加纳诊断成像学生对人工智能及其在医学成像中的应用的理解(知识)和意识水平。

IF 2.2 Q2 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING Radiology Research and Practice Pub Date : 2023-01-01 DOI:10.1155/2023/4704342
James William Ampofo, Christian Ven Emery, Ishmael Nii Ofori
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引用次数: 1

摘要

导读:最近技术的进步推动了人工智能(AI)在各个领域的应用,包括医疗保健。医学成像得益于人工智能,通过在检查、转诊协议和扫描判断中使用的算法,降低了辐射风险。这项研究工作评估了来自加纳公立大学的225名二至四年级医学影像学学生对人工智能及其在医学影像学中的前景的知识和意识水平。方法:这是一项横断面定量研究设计,采用封闭式问卷和二分法问题,在谷歌表格上设计,并通过各种班级WhatsApp平台分发给学生。将回复输入到Excel电子表格中,并使用社会科学统计软件包(SPSS) 25.0版本和Microsoft Excel 2016版本进行分析。结果:应答率为80.44%(181/225),其中男性97例(53.6%),女性82例(45.3%),不愿透露性别2例(1.1%)。其中133人(73.5%)知道人工智能已被纳入当前的成像方式,143人(79.0%)知道人工智能在医学成像中的出现。然而,只有97家(53.6%)意识到人工智能在加纳放射摄影行业的逐渐出现。此外,160人(88.4%)表示有兴趣更多地了解人工智能及其在医学成像中的应用。不到三分之一(32%)的人了解人工智能在患者定位和方案选择中的一般基本应用。近三分之二(65%)的人由于将人工智能技术纳入医疗成像设备而感到威胁或不确定自己的工作保障。不到一半(38%和43%)的参与者分别承认,目前的临床实习帮助他们认识到人工智能在医学成像中的作用,或提高了他们在人工智能方面的知识水平。讨论。总体来看,医学影像学学生对人工智能及其在医学影像学中的应用前景有一定的了解,但缺乏深入的了解。然而,他们对人工智能在加纳放射学实践中的出现缺乏必要的认识。他们还表现出对人工智能在现代成像设备中的一些基本应用缺乏了解。此外,他们对人工智能在放射技师的工作中所扮演的角色存在一定程度的误解。结论:决策者应实施教育政策,将人工智能教育融入当前的医学影像课程,为学生的未来做好准备。学生还应该实际接触到人工智能技术在当前医学成像设备中的各种结合。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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Assessing the Level of Understanding (Knowledge) and Awareness of Diagnostic Imaging Students in Ghana on Artificial Intelligence and Its Applications in Medical Imaging.

Introduction: Recent advancements in technology have propelled the applications of artificial intelligence (AI) in various sectors, including healthcare. Medical imaging has benefited from AI by reducing radiation risks through algorithms used in examinations, referral protocols, and scan justification. This research work assessed the level of knowledge and awareness of 225 second- to fourth-year medical imaging students from public universities in Ghana about AI and its prospects in medical imaging.

Methods: This was a cross-sectional quantitative study design that used a closed-ended questionnaire with dichotomous questions, designed on Google Forms, and distributed to students through their various class WhatsApp platforms. Responses were entered into an Excel spreadsheet and analyzed with the Statistical Package for the Social Sciences (SPSS) software version 25.0 and Microsoft Excel 2016 version.

Results: The response rate was 80.44% (181/225), out of which 97 (53.6%) were male, 82 (45.3%) were female, and 2 (1.1%) preferred not to disclose their gender. Among these, 133 (73.5%) knew that AI had been incorporated into current imaging modalities, and 143 (79.0%) were aware of AI's emergence in medical imaging. However, only 97 (53.6%) were aware of the gradual emergence of AI in the radiography industry in Ghana. Furthermore, 160 people (88.4%) expressed an interest in learning more about AI and its applications in medical imaging. Less than one-third (32%) knew about the general basic application of AI in patient positioning and protocol selection. And nearly two-thirds (65%) either felt threatened or unsure about their job security due to the incorporation of AI technology in medical imaging equipment. Less than half (38% and 43%) of the participants acknowledged that current clinical internships helped them appreciate the role of AI in medical imaging or increase their level of knowledge in AI, respectively. Discussion. Generally, the findings indicate that medical imaging students have fair knowledge about AI and its prospects in medical imaging but lack in-depth knowledge. However, they lacked the requisite awareness of AI's emergence in radiography practice in Ghana. They also showed a lack of knowledge of some general basic applications of AI in modern imaging equipment. Additionally, they showed some level of misconception about the role AI plays in the job of the radiographer.

Conclusion: Decision-makers should implement educational policies that integrate AI education into the current medical imaging curriculum to prepare students for the future. Students should also be practically exposed to the various incorporations of AI technology in current medical imaging equipment.

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来源期刊
Radiology Research and Practice
Radiology Research and Practice RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING-
自引率
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发文量
17
审稿时长
17 weeks
期刊介绍: Radiology Research and Practice is a peer-reviewed, Open Access journal that publishes articles on all areas of medical imaging. The journal promotes evidence-based radiology practice though the publication of original research, reviews, and clinical studies for a multidisciplinary audience. Radiology Research and Practice is archived in Portico, which provides permanent archiving for electronic scholarly journals, as well as via the LOCKSS initiative. It operates a fully open access publishing model which allows open global access to its published content. This model is supported through Article Processing Charges. For more information on Article Processing charges in gen
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