Tang

et al., 2022

[34]

China

21,785 NBI (narrow-band imaging) images and 20 videos

NBI

NBI AI system

The AI system achieved better diagnostic performance (accuracy: 79.5%, 95% CI: 77.8% - 81.0%) compared to senior (93.2%, 95% CI: 90.0% - 94.9%) and junior (85.9%, 95% CI: 84.2% - 87.4%) endoscopists.

The NBI AI system outperformed endoscopists and has the potential to improve diagnostic rates in real-time diagnosis by physicians.

Bang

et al., 2021

[35]

South Korea

2703 patients (967 ESD [endoscopic submucosal dissection], 1736 surgery)

Each dataset was written in .csv file format

ML classifier

XGBoost classifier demonstrated the best performance with an accuracy of 93.4%, recall of 99.0%, and F1 score of 95.7%.

XGBoost classifier showed high recognition capability for curative resection in undifferentiated early gastric cancer, considering variables such as patient age, sex, endoscopic lesion size, morphology, and presence/absence of ulcer.

Kuroda

et al., 2022

[36]

Japan

171 cases

Robot-assisted gastric resection using ultrasonic shears and conventional robot-assisted gastric resection using conventional forceps

Robot

The console time (310 minutes [interquartile range (IQR), 253 - 369 minutes] vs. 332 minutes [IQR, 294 - 429 minutes]; p = 0.022) and console time for gastric resection (222 minutes [IQR, 177 - 266 minutes] vs. 247 minutes [IQR, 208 - 321 minutes]; p = 0.004) were significantly shorter in the ultrasonic shears group compared to the conventional forceps group.

The ultrasonic shears robot showed better performance in robot-assisted gastric resection for gastric cancer.