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

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...

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Detalles Bibliográficos
Publicado en:South African Journal of Radiology Vol. 29; no. 1; pp. 1 - 7
Autores principales: Nciki, Ayanda I., Hlabangana, Linda T.
Formato: research tables/charts Journal Article
Publicado: African Online Scientific Information System PTY LTD 2025
Acceso en línea:Ver este registro en EBSCOhost
Descripción
Sumario: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.