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©The Author(s) 2023.
World J Gastroenterol. Dec 28, 2023; 29(48): 6198-6207
Published online Dec 28, 2023. doi: 10.3748/wjg.v29.i48.6198
Published online Dec 28, 2023. doi: 10.3748/wjg.v29.i48.6198
Table 4 A comparative summary of the state-of-the-art approaches for the binary classification of Barrett’s esophagus
| Ref. | Validation (train:valid:test) | Valid | Test |
| Ebigbo et al[33], 2020 | Holdout; Image (129:N/A:62); Test patients:14 | ACC: N/A | ACC: 89.9% |
| AUC: N/A | AUC: N/A | ||
| SEN: N/A | SEN: 83.7% | ||
| SPE: N/A | SPE: 100.0% | ||
| PPV: N/A | PPV: N/A | ||
| NPV: N/A | NPV: N/A | ||
| Hussein et al[26], 2022 | Holdout; Video (64:11:44); Patients: 118 | ACC: N/A | ACC: N/A |
| AUC: N/A | AUC: 93% | ||
| SEN: N/A | SEN: 91% | ||
| SPE: N/A | SPE: 79% | ||
| PPV: N/A | PPV: N/A | ||
| NPV: N/A | NPV: N/A | ||
| Abdelrahim et al[25], 2023 | Holdout; Image (816:471:N/A); Video (161:N/A:75); Case (161:34:75) | ACC: 94.7% | ACC: 92.0% |
| AUC: 0.898 | AUC: 0.964 | ||
| SEN: 95.3% | SEN: 93.8% | ||
| SPE: 94.5% | SPE: 90.7% | ||
| PPV: 83.6% | PPV: 88.2% | ||
| NPV: 98.6% | NPV: 95.1% | ||
| Our approach, 2023 | Holdout image; Image (771:193:160); Case (579:145:86) | ACC: 97.41% | ACC: 94.37% |
| AUC: 97.01% | AUC: 94.37% | ||
| SEN: 96.15% | SEN: 94.29% | ||
| SPE: 97.87% | SPE: 94.44% | ||
| PPV: 94.00% | PPV: 92.96% | ||
| NPV: 98.57% | NPV: 95.51% |
- Citation: Tsai MC, Yen HH, Tsai HY, Huang YK, Luo YS, Kornelius E, Sung WW, Lin CC, Tseng MH, Wang CC. Artificial intelligence system for the detection of Barrett’s esophagus. World J Gastroenterol 2023; 29(48): 6198-6207
- URL: https://www.wjgnet.com/1007-9327/full/v29/i48/6198.htm
- DOI: https://dx.doi.org/10.3748/wjg.v29.i48.6198