Please use this identifier to cite or link to this item: https://www.um.edu.mt/library/oar/handle/123456789/145872
Title: Healthcare professionals’ perception about use of AI in diagnostic imaging : a systematic review
Authors: Tancic, Jelena (2025)
Keywords: Artificial intelligence -- Medical applications
Medical informatics
Machine learning
Medical personnel -- Attitudes
Systematic reviews (Medical research)
Issue Date: 2025
Citation: Tancic, J. (2025). Healthcare professionals’ perception about use of AI in diagnostic imaging : a systematic review (Bachelor’s dissertation).
Abstract: Purpose: The aim of this study was to systematically review the literature to investigate healthcare professionals’ perceptions, attitudes, and knowledge relating to the use of AI in diagnostic imaging. Methodology: This systematic review was conducted using PRISMA guidelines. Search strategy involved using a set of predetermined keywords applied to the following databases: PubMed, Web of science (WoS), Scopus, CINAHL and Nursing and Allied health database (ProQuest). To further refine the research inclusion and exclusion criteria were established, together with search limits, such as publication years and English language. The retrieved articles were brought down from 619 to 29. Full-text studies were critically appraised using the NIH Quality Assessment Tool for observational and cross-sectional designs following data extraction process. Thematic synthesis was applied to identify recurring themes across the findings. Results Across the included literature six common themes were identified: perceptions and attitudes; Knowledge and education; Job security concerns; Trust and legal responsibility; Clinical areas to benefit the most; and a desire for professional involvement in AI. Conclusions While healthcare professionals generally had positive attitudes and perspectives towards introduction of AI in diagnostic imaging, this was closely related to their knowledge, trust and concerns of job loss due to AI. Furthermore, significant gaps in training and education among professionals were identified. Regulations, guidelines and ethical frameworks were still not established and were highlighted as a main n concern for AI use in clinical practice. Implications for Practice: Education and training in the field of AI should be promptly implemented in undergraduate and postgraduate levels. Policy makers and AI developers should include healthcare professionals in the validation step of AI tools development. Additionally, this systematic review has highlighted an urgent need for clear legal and ethical guidelines that govern the use of AI within diagnostic imaging departments and healthcare settings.
Description: B.Sc. (Hons) (Melit.)
URI: https://www.um.edu.mt/library/oar/handle/123456789/145872
Appears in Collections:Dissertations - FacHSc - 2025
Dissertations - FacHScRad - 2025

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