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©The Author(s) 2021.
Artif Intell Gastrointest Endosc. Jun 28, 2021; 2(3): 79-88
Published online Jun 28, 2021. doi: 10.37126/aige.v2.i3.79
Published online Jun 28, 2021. doi: 10.37126/aige.v2.i3.79
Table 1 List of studies evaluating role of artificial intelligence in the detection of colon polyps during the colonoscopy
Ref. | Country of origin | Study design | Results |
Fernandez-Esparrach et al[13], 2016 | Spain | Retrospective | Sensitivity 70%, Specificity 72 % |
Geetha et al[36], 2016 | India | Retrospective | Sensitivity 95%, Specificity 97% |
Misawa et al[37], 2017 | Japan | Retrospective | Accuracy higher than trainees (87.8 vs 63.4%; P = 0.01), but similar to experts (87.8 vs 84.2%; P = 0.76) |
Zhang et al[38], 2017 | China | Retrospective | Accuracy 86% |
Yu et al[39], 2017 | China | Retrospective | Sensitivity 71%, PPV 88% |
Billah et al[40], 2017 | Bangladesh | Retrospective | Sensitivity 99%, Specificity 98.5%, Accuracy 99% |
Chen et al[23], 2018 | Taiwan | Retrospective | Sensitivity 96.3%, Specificity 78.1% |
Urban et al[18], 2018 | United States | Retrospective | Accuracy 96.4% |
Misawa et al[17], 2018 | Japan | Retrospective | Sensitivity, Specificity, and Accuracy were 90%, 63%, and 76%, respectively |
Wang et al[19], 2018 | China | Retrospective | Sensitivity 94.38%, Specificity 95.92% |
Su et al[41], 2019 | China | Prospective | Polyp detection rate was 38.3% as compared to 25.4% in control group (P < 0.001) |
Wang et al[42], 2019 | China | Prospective | Polyp detection rate was 45% as compared to 29% in the control group (P < 0.001) |
Klare et al[43], 2019 | Germany | Prospective | Larger polyp detection, Odds ration 2.71, P = 0.042 |
Figueiredo et al[44], 2019 | Portugal | Retrospective | Sensitivity 99.7%, Specificity 84.9%, Accuracy 91.1% |
Yamada et al[45], 2019 | Japan | Retrospective | Sensitivity 97.3%, Specificity: 99% |
Lee[46], 2020 | South Korea | Retrospective | Accuracy 93.4%, Sensitivity 89.9%, Specificity 93.7% |
Luo et al[16], 2020 | China | Prospective | Polyp detection rate for diminutive polyps increased (38.7% vs 34%, P < 0.001). No difference was found for larger polyps |
Gong[47], 2020 | China | Prospective | Polyp detection rate was 47% as compared to 34% in control group (P = 0.0016) |
Liu et al[48], 2020 | China | Prospective | Polyp detection rate was 44% as compared to 28% in control group (P < 0.001) |
Ozawa et al[49], 2020 | Japan | Retrospective | Sensitivity 92%, PPV 86%, Accuracy 83% |
Wang et al[50], 2020 | China | Prospective | Polyp detection rate was 52% as compared to 37% in control group (P < 0.0001) |
Hasssan et al[51], 2020 | Italy | Retrospective | Sensitivity 99.7% |
Repici et al[52], 2020 | Italy | Prospective | Adenoma detection rate was 54.8% as compared to 40.4% in control group (P < 0.001) |
- Citation: Shah N, Jyala A, Patel H, Makker J. Utility of artificial intelligence in colonoscopy. Artif Intell Gastrointest Endosc 2021; 2(3): 79-88
- URL: https://www.wjgnet.com/2689-7164/full/v2/i3/79.htm
- DOI: https://dx.doi.org/10.37126/aige.v2.i3.79