Table 2.

Number of embolism events according to X-ray computed microtomography (µCT) and linear discriminant analysis (LDA) model for the 132 AE datasets of sensor AE₁

AE dataset	µCT	LDA	AE dataset	µCT	LDA
1–2	0–2	0–0	67–68	1–0	1–0
3–4	0–2	0–0	69–70	76–0	85–5
5–6	0–1	1–0	71–72	1–0	1–1
7–8	0–29	0–44	73–74	1–0	1–1
9–10	0–6	10–1	75–76	1–0	2–1
11–12	0–9	2–1	77–78	1–0	1–6
13–14	0–3	0–1	79–80	33–0	1–2
15–16	0–1	9–0	81–82	28–0	1–5
17–18	0–1	1–0	83–84	1–0	1–3
19–20	3–0	1–0	85–86	4–0	2–3
21–22	1–0	0–1	87–88	1–0	1–1
23–24	5–0	1–1	89–90	1–0	1–1
25–26	1–0	1–2	91–92	1–0	1–16
27–28	1–0	1–5	93–94	5–0	2–3
29–30	1–0	1–1	95–96	1–0	0–2
31–32	2–0	1–1	97–98	1–0	1–3
33–34	1–0	1–2	99–100	1–0	1–14
35–36	2–0	0–1	101–102	1–0	1–0
37–38	1–0	0–3	103–104	32–1	2–4
39–40	2–0	1–2	105–106	0–6	2–1
41–42	6–0	2–12	107–108	0–4	1–4
43–44	15–0	4–1	109–110	0–1	11–1
45–46	3–0	1–1	111–112	3–0	5–4
47–48	1–0	5–11	113–114	1–0	4–10
49–50	1–19	1–4	115–116	2–0	1–1
51–52	0–2	4–1	117–118	1–4	1–5
53–54	1–0	4–1	119–120	0–62	14–73
55–56	8–0	1–1	121–122	0–16	9–0
57–58	1–0	5–0	123–124	12–0	1–0
59–60	1–0	1–2	125–126	2–0	1–4
61–62	1–0	1–1	127–128	1–0	1–1
63–64	1–0	5–1	129–130	1–0	1–8
65–66	14–0	1–1	131–132	1–0	1–7

Italic values illustrate sufficient embolism-related AE detection by LDA in accordance with the number of embolism events by µCT. For every AE dataset, an LDA model was trained on all remaining datasets