Table 2.

Pediatric Focused Assessment With Sonography for Trauma View Classification Accuracy by the Deep Learning Model for (A) Video Clips and (B) Still Frames

(A) Class-Specific Accuracy for Video Clips
Expert Labels	Deep Learning Model Predicted Class
	Cardiac	Pleural	Upper quadrant	Suprapubic
Cardiac	80	0	0	0	Model overall accuracy
Pleural	0	53	0	1	97.8 (96.0–99.0)
Upper quadrant	5	0	194	1	F-Score
Suprapubic	1	0	2	122	0.978
					Brier’s score
					0.378
Sensitivity	100 (94.3–100)	98.1 (88.8–99.9)	97.0 (93.3–98.8)	97.6 (92.6–99.4)
Specificity	98.4 (96.4–99.4)	100 (98.8–100)	99.2 (96.9–99.9)	99.4 (97.6–99.9)
Accuracy	98.7 (97.0–99.5)	99.8 (98.4–100)	98.3 (96.5–99.2)	98.9 (97.3–99.6)
(B) Class-Specific Accuracy for Still Frames
Expert Labels	Deep Learning Model Predicted Class
	Cardiac	Pleural	Upper quadrant	Suprapubic
Cardiac	19,970	12	462	792	Model overall accuracy
Pleural	28	7377	8	84	93.4 (93.3–93.6)
Upper quadrant	1989	79	43,524	1770	F-score
Suprapubic	882	13	732	26,498	0.935
					Brier’s score
					0.394
Sensitivity	94.0 (93.7–94.4)	98.4 (98.1–98.7)	91.9 (91.7–92.1)	94.2 (93.9–94.5)
Specificity	96.5 (96.4–93.6)	99.9 (99.9–99.9)	97.9 (97.8–98.0)	96.5 (96.4–96.7)
Accuracy	96.0 (95.9–96.1)	99.8 (99.8–99.8)	95.2 (95.0–95.3)	95.9 (95.8–96.0)

Note: Boldface indicates diagnostic test characteristics and non-boldface indicates “n” per cell.