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...
| Publicado en: | South African Journal of Radiology Vol. 29; no. 1; pp. 1 - 7 |
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| Autores principales: | , |
| Formato: | research tables/charts Journal Article |
| Publicado: |
African Online Scientific Information System PTY LTD
2025
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=190688913&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 190688913 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 1027202X 39WP jtl: South African Journal of Radiology issn: 1027202X maglogo: N pubinfo: dt: 2025 vid: 29 iid: 1 pid: 56831 pub: African Online Scientific Information System PTY LTD place: , <Blank> artinfo: ui: 190688913 190688913 190688913 10.4102/sajr.v29i1.3026 190688913 ppf: 1 ppct: 6 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Perceptions and attitudes towards AI among trainee and qualified radiologists at selected South African training hospitals. aug: au: Nciki, Ayanda I. Hlabangana, Linda T. affil: Department of Radiology, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa sug: subj: Radiologists Psychosocial Factors Interns and Residents Psychosocial Factors Artificial Intelligence Utilization Academic Medical Centers Attitude of Health Personnel Human South Africa Male Female Adult Cross Sectional Studies Multicenter Studies Surveys Questionnaires Purposive Sample Confidence Intervals Data Analysis Software Professional Knowledge Artificial Intelligence Education Diagnostic Imaging Machine Learning Software Skill Acquisition Adult: 19-44 years Male Female ab: 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. pubtype: Academic Journal doctype: research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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