Singapore radiographers' perceptions and expectations of artificial intelligence - A qualitative study

Stakeholder perspectives towards diagnostic artificial intelligence: a co-produced qualitative evidence synthesis

“…Across 44 studies, 689 participants were interviewed and 402 participated in focus groups. 31 studies conducted interviews, 16 , 24 , 25 , 31 , 32 , 34 , 36 , 37 , 38 , 40 , 41 , 42 , 43 , 44 , 45 , 48 , 49 , 50 , 51 , 53 , 55 , 57 , 59 , 60 , 61 , 62 , 63 , 64 nine conducted focus groups, 18 , 26 , 27 , 29 , 30 , 33 , 52 , 56 , 58 , 65 five conducted ethnographic studies with interviews, 17 , 46 , 47 , 54 , 66 and two conducted both interviews and focus groups. 35 , 47 The mean number of participants in interview studies was 20 (IQR 15–24), and in focus groups 40(IQR 15–37).…”

“… Ng et al. (2022) 52 Qualitative, Phenomenology/thematic analysis Focus groups Radiographers working in public institutions in Singapore, purposive sampling 22 11 (50%) female; age 23–42 years old (median 30.5 years); working experience 1–18 years (median six years) Radiology Hypothetical AI used in radiography Four themes were developed from the data: 1. Knowledge of AI and its applications, 2.…”

“…Four distinct stakeholder groups were described: patients/the public, clinicians, researchers, and healthcare leaders. Twenty studies focussed on clinician perspectives, 17 , 18 , 29 , 32 , 35 , 42 , 44 , 46 , 48 , 50 , 52 , 54 , 55 , 60 , 61 , 63 eight on patients, 16 , 26 , 27 , 30 , 33 , 40 , 53 , 57 , 58 and one on researchers 59 and healthcare leaders/experts. 45 Fourteen focussed on mixed groups.…”

“… 45 Fourteen focussed on mixed groups. 24 , 25 , 31 , 34 , 36 , 38 , 39 , 41 , 47 , 51 , 56 , 65 , 66 , 67 Of 29 studies exploring clinician perspectives, 26 included doctors, 17 , 18 , 24 , 25 , 31 , 32 , 34 , 35 , 36 , 37 , 38 , 39 , 41 , 42 , 44 , 46 , 47 , 48 , 55 , 56 , 59 , 60 , 61 , 63 , 65 , 66 six included allied healthcare professionals, 29 , 35 , 37 , 42 , 52 , 60 and two included nurses. 38 , 44 …”

Knowledge, perceptions, and expectations of Artificial intelligence in radiography practice: A global radiography workforce survey

“…Additionally, a lack of appreciation of the different operational aspects of radiography AI will affect, beyond report and image interpretation, adds to the uncertainty. For example, the recent study by Ng and colleagues [54] that explored the perceptions and expectations of AI among Singaporean radiographers reported that participants envisioned several applications across different phases of clinical workflows including order vetting, patient positioning, language translation, and artefact removal. Thus, scientifically sound, prospective studies are needed to provide the necessary evidence base to support these findings within radiography practice.…”