Using AI to assess surgical performance: study
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A research team has succeeded in proving that artificial intelligence can reliably assess surgeons' skills. A method involving a three-stage procedure has been presented that correctly designates good and mediocre performance with a high accuracy rate. This paves the way for further steps towards AI-supported expert systems.

Currently, the assessment of surgical skills is a manual and time-consuming process that is prone to subjective interpretation. This study aims to automate surgical skill assessment in laparoscopic cholecystectomy videos using machine learning algorithms.

To address this, a three-stage machine learning method is proposed: first, a Convolutional Neural Network was trained to identify and localize surgical instruments. Second, motion features were extracted from the detected instrument localizations throughout time. Third, a linear regression model was trained based on the extracted motion features to predict surgical skills.

This three-stage modeling approach achieved an accuracy of 87±0.2% in distinguishing good versus poor surgical skill.

Conclusively, while the technique cannot reliably quantify the degree of surgical skill yet it represents an important advance towards automation of surgical skill assessment.

Scientific Reports
Source: https://doi.org/10.1038/s41598-021-84295-6
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