Table 4.

Showing the differences in acquisition time between the formula, operator decision and the deep learning

Acquisition time (s)	Formula vs operator			Formula vs deep learning			Operator vs deep learning
	Mean diff	P-value	95% CI of diff	Mean diff	P-value	95% CI of diff	Mean diff	P-value	95% CI of diff
All	5 ± 59	0.68	− 18, 27	9 ± 89	0.58	− 24, 42	5 ± 57	0.66	− 17, 26
Healthy	− 15 ± 40	0.04	− 30, − 1	− 26 ± 66	0.04	− 50, − 1	− 10 ± 64	0.39	− 34, 14
Patient (standardised AW)	13 ± 19	< 0.01	6, 20	14 ± 25	0.01	4, 23	0 ± 18	0.90	− 6, 7
Patient (variable AW)	16 ± 90	0.35	− 18, 49	39 ± 129	0.11	− 9, 87	23 ± 69	0.07	− 2, 49

	Formula			Operator			Deep learning
	Mean diff	P-value	95% CI of diff	Mean diff	P-value	95% CI of diff	mean diff	P-value	95% CI of diff
Healthy vs patient (all)	10 (54)	0.85	− 101, 121	40 (47)	0.40	− 57, 137	62 (46)	0.19	− 34, 158
Patient (standardised AW) vs patient (variable AW)	213 (50)	< 0.01	106, 321	216 (33)	< 0.01	146, 286	239 (31)	< 0.01	174, 303

This is further compared between the whole cohort and the healthy and patient participants. The mean difference was analysed using a one-sample t-test and presented as mean ± SD. Unpaired data was analysed using Welch’s t test and presented as mean and standard error. Statistically significant values (p<0.05) are indicated in bold