Table 2. Recent works of AI-assisted application in other surgery.
Study | Year | Operations | No. of video | Applications | Performance |
---|---|---|---|---|---|
Matava et al. (24) | 2020 | Laryngoscopy and bronchoscopy | 775 | Anatomy classification in real-time | Overall confidence of classification ranges 0.54 to 0.84 |
Kitaguchi et al. (26) | 2020 | Colorectal surgery | 300 | Surgical phase, action, and tool recognition | Accuracy of 81.0%, 83.2%, and 51.2% respectively |
Madad Zadeh et al. (27) | 2020 | Hysterectomy | 461 images | Anatomy detection | Accuracy of 24–97% |
Morita et al. (54) | 2019 | Cataract surgery | 303 | Surgical phase recognition | Mean correct response rate of 96.5% |
Bodenstedt et al. (55) | 2019 | Laparoscopic procedure | 80 | Surgical duration prediction | Overall average error of 37% |
Hashimoto et al. (56) | 2019 | Gastrectomy | 88 | Surgical phase recognition | Accuracy of 82% |
Korndorffer et al. (57) | 2020 | Cholecystectomy | 1,051 | CVS and intraoperative events evaluation | Accuracy of 75%, and 99% |
Mascagni et al. (59) | 2020 | Cholecystectomy | 100 | Formalization of video reporting of CVS | Kappa scores of inter-rater agreements by binary assessment is 0.75 |
Yamazaki et al. | 2020 | Gastrectomy | 52 | Surgical tool detection | Accuracy 86% accuracy |
AI, artificial intelligence; CVS, critical view of safety.