Artificial intelligence-assisted colonoscopy: Transforming detection, characterization, and management of colorectal neoplasia

Table 1 Comparative table of the effectiveness of artificial intelligence in the detection of colorectal neoplasms

Ref.	Design	ADR (AI vs control)	P value	PDR (AI vs control)	P value
Wang et al[14]	Double-blind RCT	34% vs 28%	0.03	Not reported
Repici et al[15]	Multicenter RCT	54.8% vs 40.4%	< 0.001	Not reported
Liu et al[16]	Prospective RCT	39.1% vs 23.9%	< 0.001	43.7% vs 27.8%	< 0.001

ADR: Adenoma detection rate; AI: Artificial intelligence; PDR: Polyp detection rate; RCT: Randomized controlled trial.

Table 2 Comparative table of the use of artificial intelligence in the characterization of colorectal neoplasms

Ref.	Design	AI vs comparator	Diagnostic accuracy (AI vs human)	P value	Sensitivity (%)	Specificity (%)
Byrne et al[23]	Prospective real-time	AI vs expert endoscopists	94% vs 91%	0.16	98	83
Kudo et al[24]	Multicenter diagnostic	AI vs histology	98.0% (stained)/96.0% (NBI)	Not reported	96.9	94-100
Mori et al[25]	Prospective	AI vs expert endoscopists	92% vs 80%-85%	> 0.05	98	83

AI: Artificial intelligence; NBI: Narrow-band imaging.