Artificial intelligence in colonoscopy

Table 7 Endocytoscopy

Ref.	Study design	Algorithm type	Dataset	Results
Mori et al[54]	Pilot study	CAD using EC-CAD	176 colorectal polyps from 152 patients	Accuracy: 89.2%
				Sensitivity: 92%
				Specificity 79.5%
Takeda et al[55]	Retrospective study	CAD using EC-CAD	5543 endocytoscopy images for machine learning. 200 test images	Overall
				Accuracy: 94%
				Sensitivity: 89.4%
				Specificity: 98.9%
				PPV: 98.8%
				NPV: 90.1%
				High-confidence diagnosis
				Accuracy: 99.3%
				Sensitivity: 98.1%
				Specificity: 100%
				PPV: 100%
				NPV: 98.8%
Mori et al[33]	Single-group, open-label, prospective study	Real-time CAD during colonoscopy	466 diminutive polyps from 325 patients	Accuracy: 98.1%
				Sensitivity 93.8%
				Specificity 90.3%
				PPV 94.1%
				NPV 89.8%
Kudo et al[56]	Retrospective study	CAD using EndoBRAIN	100 polyps from 89 patients	Accuracy: 98%
				Sensitivity 96.9%
				Specificity 100%
				PPV 100%
				NPV 94.6%

CAD: Computer-aided diagnosis.