Artificial intelligence for characterization of diminutive colorectal polyps: A feasibility study comparing two computer-aided diagnosis systems

doi:10.37126/aige.v5.i1.90574

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Mar 8, 2024 (publication date) through Jul 22, 2024

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Artificial Intelligence in Gastrointestinal Endoscopy

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2689-7164

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Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA

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Artif Intell Gastrointest Endosc. Mar 8, 2024; 5(1): 90574
Published online Mar 8, 2024. doi: 10.37126/aige.v5.i1.90574

Table 3 Diagnostic performances of artificial intelligence for ColoRectal polyps in different image enhancement modes

	AI4CRP (n = 51)
	BLI, % (95%CI)	HDWL, % (95%CI)	LCI, % (95%CI)	Multimodal imaging, % (95%CI)
Sensitivity	82.1 (0.66-0.92)	59.0 (0.42-0.74)	76.9 (0.60-0.88)	71.8 (0.55-0.84)
Specificity	75.0 (0.43-0.93)	91.7 (0.60-1.00)	83.3 (0.51-0.97)	91.7 (0.60-1.00)
PPV	91.4 (0.76-0.98)	95.8 (0.77-1.00)	93.8 (0.78-0.99)	96.6 (0.80-1.00)
NPV	56.3 (0.31-0.79)	40.7 (0.23-0.61)	52.6 (0.29-0.75)	50.0 (0.29-0.71)
Diagnostic accuracy	80.4 (0.66-0.90)	66.7 (0.52-0.79)	78.4 (0.64-0.88)	76.5 (0.62-0.87)

AI4CRP: Artificial intelligence for ColoRectal polyps; BLI: Blue light imaging; CI: Confidence interval; HDWL: High definition white light; LCI: Linked color imaging; NPV: Negative predictive value; PPV: Positive predictive value.

Citation: van der Zander QEW, Schreuder RM, Thijssen A, Kusters CHJ, Dehghani N, Scheeve T, Winkens B, van der Ende - van Loon MCM, de With PHN, van der Sommen F, Masclee AAM, Schoon EJ. Artificial intelligence for characterization of diminutive colorectal polyps: A feasibility study comparing two computer-aided diagnosis systems. Artif Intell Gastrointest Endosc 2024; 5(1): 90574
URL: https://www.wjgnet.com/2689-7164/full/v5/i1/90574.htm
DOI: https://dx.doi.org/10.37126/aige.v5.i1.90574