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. 2022 Sep 15;71(12):2388–2390. doi: 10.1136/gutjnl-2021-326470

Table 1.

Performance results of the AI-CDSS in the internal cross validation and the test data set: IoU and Dice Score for all categories as well as their means across all categories, pixel accuracy for complete frames and 95% CI in brackets

Internal cross validation
Vessel detection Tissue differentiation Instrument detection
Vessel Submucosa Muscularis Background Instrument Knife Mean
Dice Score 55.15
(54.10 to 56.18)
75.51
(74.88 to 76.12)
70.64
(69.32 to 71.88)
86.49
(85.99 to 86.99)
88.69
(87.57 to 89.83)
80.60
(79.61 to 81.49)
76.18
(75.73 to 76.57)
IoU 38.07
(37.08 to 39.07)
60.65
(59.85 to 61.44)
54.60
(53.05 to 56.10)
76.19
(75.43 to 76.98)
79.68
(77.89 to 81.54)
67.51
(66.13 to 68.77)
62.78
(62.18 to 63.31)
Pixel accuracy 80.99
(80.52 to 81.47)
Test
Dice Score 62.77
(60.08 to 65.12)
80.71
(79.50 to 81.82)
72.48
(69.40 to 74.99)
91.39
(90.45 to 92.10)
89.69
(87.09 to 91.96)
83.50
(82.06 to 84.87)
80.09
(79.14 to 80.92)
IoU 45.74
(42.94 to 48.28)
67.65
(65.97 to 69.24)
56.84
(53.14 to 59.99)
84.14
(82.56 to 85.36)
81.30
(77.14 to 85.11)
71.67
(69.58 to 73.72)
67.89
(66.61 to 69.04)
Pixel accuracy 86.89
(85.86 to 87.70)

AI-CDSS, artificial intelligence clinical decision support solution.