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Singapore radiographers' perceptions and expectations of artificial intelligence: a qualitative study

2022-12Artigo científico Acesso aberto
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dc.contributor.authorNg, Chloe Theresia
dc.contributor.authorRoslan, Sri Nur Aidah
dc.contributor.authorChng, Yi Hong
dc.contributor.authorChoong, Denise Ai Wen
dc.contributor.authorChong, Ai Jia Letty
dc.contributor.authorTay, Yi Xiang
dc.contributor.authorLança, Luís
dc.contributor.authorChua, Eric Chern-Pin
dc.date.accessioned2022-09-19T10:53:31Z
dc.date.available2024-09-19T00:30:20Z
dc.date.issued2022-12
dc.description.abstractIntroduction: With the emergence of artificial intelligence (AI) in medical imaging, radiographers are likely to be at the forefront of this technological advancement. Studies have therefore been conducted recently to understand radiographers’ opinions on AI adoption. This study extends that work by using a qualitative approach to further explore radiographers’ knowledge, perceptions, and expectations of AI. Method: Six online focus groups were conducted with 22 radiographers from the three public healthcare clusters in Singapore. They were purposively sampled, and participants were recruited from a broad demographic background with varying years of working experience and designations. The focus group sessions were transcribed verbatim and thematic analysis was performed on their responses. Results: Participants demonstrated limited knowledge of AI. Their perceptions of AI were mixed, recognising its benefits in increasing efficiency and improving patient care, but also aware of its limitations in accuracy and bias. On how patients may perceive AI, participants felt that patients would accept AI if they felt it improves their care but may reject it once they lose trust in it. Expectations-wise, participants envisioned several applications in pre-, peri‑, and post-procedural workflows including order vetting, patient positioning, language translation, and artifact removal. On radiographers’ role and career opportunities, some participants see an opportunity for radiographers to specialise in AI, becoming involved in algorithm development and its clinical implementation. Discussion: Our findings suggest that widespread implementation of AI would require limited knowledge amongst radiographers and current AI limitations to be addressed. While radiographers are positively anticipating the integration of AI into their practices, they should also become actively involved in the development of AI tools such that those they envisioned. This would help align the optimal use of AI tools and radiographer role changes. Patients’ acceptance and reactions to AI also warrant further research.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationNg CT, Roslan SN, Chng YH, Choong DA, Chong AJ, Lança L, et al. Singapore radiographers' perceptions and expectations of artificial intelligence: a qualitative study. J Med Imaging Radiat Sci. 2022;53(4):554-63.pt_PT
dc.identifier.doi10.1016/j.jmir.2022.08.005pt_PT
dc.identifier.urihttp://hdl.handle.net/10400.21/14973
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherElsevierpt_PT
dc.relation.publisherversionhttps://www.sciencedirect.com/science/article/pii/S1939865422003393pt_PT
dc.subjectArtificial intelligencept_PT
dc.subjectRadiographypt_PT
dc.subjectRadiographerspt_PT
dc.subjectFocus group discussionpt_PT
dc.subjectSingaporept_PT
dc.titleSingapore radiographers' perceptions and expectations of artificial intelligence: a qualitative studypt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.citation.endPage563pt_PT
oaire.citation.issue4pt_PT
oaire.citation.startPage554pt_PT
oaire.citation.titleJournal of Medical Imaging and Radiation Sciencespt_PT
oaire.citation.volume53pt_PT
rcaap.rightsopenAccesspt_PT
rcaap.typearticlept_PT

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