Table 4.

Level of Agreement Concerning the Usefulness of AI-Based Applications in Clinical Practice

	Strongly Agree N (%) Code = 1	Agree N (%) Code = 2	Neither Agree Nor Disagree N (%) Code = 3	Disagree N (%) Code = 4	Strongly Disagree N (%) Code = 5	95% Confidence Interval	Median	Total
AI is useful in clinical decision making such as justification of examination	60 (26.8%)	96 (42.9%)	46 (20.5%)	16 (7.2%)	6 (2.6%)	(2.03–2.29)	2	224 (100%)
AI is useful in automated imaging protocol selection according to clinical question and patient condition	46 (20.5%)	102 (45.6%)	48 (21.4%)	22 (9.9%)	6 (2.6%)	(2.16–2.42)	2	224 (100%)
AI will be useful in improving diagnosis and saving time	74 (33%)	94 (42.1%)	38 (16.8%)	16 (7.2%)	2 (0.9%)	(1.89–2.13)	2	224 (100%)
AI assists in personalizing imaging for patients such as tracking radiation and follow up examinations	40 (17.9%)	116 (51.7%)	40 (17.9%)	24 (10.7%)	4 (1.8%)	(2.14–2.39)	2	224 (100%)