Original Research Perceptions and attitudes towards AI among trainee and qualified radiologists at selected South African training hospitals

Ayanda I. Nciki, Linda T. Hlabangana

About the author(s) Ayanda I. Nciki, Department of Radiology, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
Linda T. Hlabangana, Department of Radiology, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa

Abstract

Background: Artificial intelligence (AI) is transforming industries, but its adoption in healthcare, especially radiology, remains contentious.

Objectives: This study evaluated the perceptions and attitudes of trainee and qualified radiologists towards the adoption of AI in practice.

Method: A cross-sectional survey using a paper-based questionnaire was completed by trainee and qualified radiologists. Survey questions covered AI knowledge, perceptions, attitudes, and AI training in the registrar programme on a 3-point Likert scale.

Results: A total of 100 participants completed the survey; 54% were aged 26–65 years and 61% were female, with none currently using AI in daily radiology practice. The majority (78%) of participants understood the basics and knew the role of AI in radiology. Most knew about AI from media reports (77%) and majority (95%) were never involved in AI training; only 3% of participants had no knowledge of AI at all. Participants agreed that AI could reliably detect pathological conditions (89%), reach reliable diagnosis (89%), improve daily work (78%), and 89% favoured AI practice; 89% believed that in the future, machine learning will not be independent of the radiologist. Participants were willing to learn (98%) and contribute towards advancing AI software (97%) and agreed that AI will improve the registrars’ programme (97%), also noting that AI applications are as important as medical skills (87%).

Conclusion: The findings suggest AI in radiology is in its infancy, with a need for educational programmes to upskill radiologists.

Contribution: Participants were positive about AI implementation in practice and in the registrar learning programme.

Keywords

artificial intelligence; attitudes; perceptions; qualified radiologist; trainee radiologist

Sustainable Development Goal

Goal 3: Good health and well-being

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