Edzie Emmanuel Kobina Mesi, Dzefi-Tettey Klenam, Asemah Abdul Raman, Brakohiapa Edmund Kwakye, Asiamah Samuel, Quarshie Frank, Amankwa Adu Tutu, Raj Amrit, Nimo Obed, Boadi Evans, Kpobi Joshua Mensah, Edzie Richard Ato, Osei Bernard, Turkson Veronica, Kusodzi Henry
Department of Medical Imaging, School of Medical Sciences, College of Health and Allied Sciences, University of Cape Coast, Cape Coast, Ghana.
Department of Radiology, Korle Bu Teaching Hospital, 1 Guggisberg Avenue, Accra, Ghana.
Heliyon. 2023 Apr 19;9(5):e15558. doi: 10.1016/j.heliyon.2023.e15558. eCollection 2023 May.
The integration of Artificial Intelligence (AI)-based technologies in medicine is advancing rapidly especially in the field of radiology. This however, is at a slow pace in Africa, hence, this study to evaluate the perspectives of Ghanaian radiologists.
Data for this cross-sectional prospective study was collected between September and November 2021 through an online survey and entered into SPSS for analysis. A Mann-Whitney test assisted in checking for possible gender differences in the mean Likert scale responses on the radiologists' perspectives about AI in radiology. Statistical significance was set at P ≤ 0.05.
The study comprised 77 radiologists, with more males (71.4%). 97.4% were aware of the concept of AI, with their initial exposure via conferences (42.9%). The majority of the respondents had average awareness (36.4%) and below average expertise (44.2%) in radiological AI usage. Most of the participants (54.5%) stated, they do not use AI in their practices. The respondents disagreed that AI will ultimately replace radiologists in the near future (average Likert score = 3.49, SD = 1.096) and that AI should be an integral part of the training of radiologists (average Likert score = 1.91, SD = 0.830).
Although the radiologists had positive opinions about the capabilities of AI, they exhibited an average awareness of and below average expertise in the usage of AI applications in radiology. They agreed on the potential life changing impact of AI and were of the view that AI will not replace radiologists but serve as a complement. There was inadequate radiological AI infrastructure in Ghana.
基于人工智能（AI）的技术在医学领域的整合正在迅速推进，尤其是在放射学领域。然而，在非洲，这一进程较为缓慢，因此，开展本研究以评估加纳放射科医生的观点。
本横断面前瞻性研究的数据于2021年9月至11月通过在线调查收集，并录入SPSS进行分析。采用曼-惠特尼检验来检查放射科医生对放射学中人工智能观点的平均李克特量表反应中可能存在的性别差异。统计学显著性设定为P≤0.05。
该研究包括77名放射科医生，男性居多（71.4%）。97.4%的人知晓人工智能的概念，他们最初是通过会议接触到人工智能的（42.9%）。大多数受访者对放射学人工智能的使用有平均认知水平（36.4%）且专业知识低于平均水平（44.2%）。大多数参与者（54.5%）表示，他们在实践中不使用人工智能。受访者不同意人工智能在不久的将来最终会取代放射科医生（平均李克特得分=3.49，标准差=1.096），也不同意人工智能应成为放射科医生培训的一个组成部分（平均李克特得分=1.91，标准差=0.830）。
尽管放射科医生对人工智能的能力持积极看法，但他们对放射学中人工智能应用的使用表现出平均认知水平且专业知识低于平均水平。他们认同人工智能可能带来改变生活的影响，并认为人工智能不会取代放射科医生，而是起到补充作用。加纳的放射学人工智能基础设施不足。
