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 cro...
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| Format: | Article |
| Language: | English |
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AOSIS
2025-01-01
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| Series: | South African Journal of Radiology |
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| Online Access: | https://sajr.org.za/index.php/sajr/article/view/3026 |
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| _version_ | 1823858206977294336 |
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| author | Ayanda I. Nciki Linda T. Hlabangana |
| author_facet | Ayanda I. Nciki Linda T. Hlabangana |
| author_sort | Ayanda I. Nciki |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-8932e30b637b47cfbaef560ae3c605d0 |
| institution | Kabale University |
| issn | 1027-202X 2078-6778 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | AOSIS |
| record_format | Article |
| series | South African Journal of Radiology |
| spelling | doaj-art-8932e30b637b47cfbaef560ae3c605d02025-02-11T13:30:57ZengAOSISSouth African Journal of Radiology1027-202X2078-67782025-01-01291e1e610.4102/sajr.v29i1.30261280Perceptions and attitudes towards AI among trainee and qualified radiologists at selected South African training hospitalsAyanda I. Nciki0Linda T. Hlabangana1Department of Radiology, Faculty of Health Sciences, University of the Witwatersrand, JohannesburgDepartment of Radiology, Faculty of Health Sciences, University of the Witwatersrand, JohannesburgBackground: 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.https://sajr.org.za/index.php/sajr/article/view/3026artificial intelligenceattitudesperceptionsqualified radiologisttrainee radiologist |
| spellingShingle | Ayanda I. Nciki Linda T. Hlabangana Perceptions and attitudes towards AI among trainee and qualified radiologists at selected South African training hospitals South African Journal of Radiology artificial intelligence attitudes perceptions qualified radiologist trainee radiologist |
| title | Perceptions and attitudes towards AI among trainee and qualified radiologists at selected South African training hospitals |
| title_full | Perceptions and attitudes towards AI among trainee and qualified radiologists at selected South African training hospitals |
| title_fullStr | Perceptions and attitudes towards AI among trainee and qualified radiologists at selected South African training hospitals |
| title_full_unstemmed | Perceptions and attitudes towards AI among trainee and qualified radiologists at selected South African training hospitals |
| title_short | Perceptions and attitudes towards AI among trainee and qualified radiologists at selected South African training hospitals |
| title_sort | perceptions and attitudes towards ai among trainee and qualified radiologists at selected south african training hospitals |
| topic | artificial intelligence attitudes perceptions qualified radiologist trainee radiologist |
| url | https://sajr.org.za/index.php/sajr/article/view/3026 |
| work_keys_str_mv | AT ayandainciki perceptionsandattitudestowardsaiamongtraineeandqualifiedradiologistsatselectedsouthafricantraininghospitals AT lindathlabangana perceptionsandattitudestowardsaiamongtraineeandqualifiedradiologistsatselectedsouthafricantraininghospitals |