City Research Online

Radiographers' perspectives on the emerging integration of artificial intelligence into diagnostic imaging: The Ghana study

Ohene-Botwe, B. ORCID: 0000-0002-0477-640X, Antwi, W. K., Arkoh, S. & Akudjedu, T. N. (2021). Radiographers' perspectives on the emerging integration of artificial intelligence into diagnostic imaging: The Ghana study. Journal of Medical Radiation Sciences, 68(3), pp. 260-268. doi: 10.1002/jmrs.460


INTRODUCTION: The integration of artificial intelligence (AI) systems into medical imaging is advancing the practice and patient care. It is thought to further revolutionise the entire field in the near future. This study explored Ghanaian radiographers' perspectives on the integration of AI into medical imaging.

METHODS: A cross-sectional online survey of registered Ghanaian radiographers was conducted within a 3-month period (February-April, 2020). The survey sought information relating to demography, general perspectives on AI and implementation issues. Descriptive and inferential statistics were used for data analyses.

RESULTS: A response rate of 64.5% (151/234) was achieved. Majority of the respondents (n = 122, 80.8%) agreed that AI technology is the future of medical imaging. A good number of them (n = 131, 87.4%) indicated that AI would have an overall positive impact on medical imaging practice. However, some expressed fears about AI-related errors (n = 126, 83.4%), while others expressed concerns relating to job security (n = 35, 23.2%). High equipment cost, lack of knowledge and fear of cyber threats were identified as some factors hindering AI implementation in Ghana.

CONCLUSIONS: The radiographers who responded to this survey demonstrated a positive attitude towards the integration of AI into medical imaging. However, there were concerns about AI-related errors, job displacement and salary reduction which need to be addressed. Lack of knowledge, high equipment cost and cyber threats could impede the implementation of AI in medical imaging in Ghana. These findings are likely comparable to most low resource countries and we suggest more education to promote credibility of AI in practice.

Publication Type: Article
Additional Information: © 2021 The Authors. Journal of Medical Radiation Sciences published by John Wiley & Sons Australia, Ltd on behalf of Australian Society of Medical Imaging and Radiation Therapy and New Zealand Institute of Medical Radiation Technology This is an open access article under the terms of the Creative Commons Attribution-NonCommercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.
Publisher Keywords: Artificial intelligence; Ghana; medical Imaging; perspectives; radiographer
Subjects: R Medicine > RC Internal medicine
Departments: School of Health & Psychological Sciences > Midwifery & Radiography
Text - Published Version
Available under License Creative Commons Attribution Non-commercial.

Download (170kB) | Preview



Downloads per month over past year

View more statistics

Actions (login required)

Admin Login Admin Login