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

• Main Authors: Benard O. Botwe, William K. Antwi, Samuel Arkoh, Theophilus N. Akudjedu
• Format: Article
• Language: English
• Published: Wiley 2021-09-01
• Series: Journal of Medical Radiation Sciences
• Subjects: Artificial intelligence; Ghana; medical Imaging; perspectives; radiographer
• Online Access: https://doi.org/10.1002/jmrs.460
• ISSN: 2051-3895; 2051-3909

Abstract 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.