Assessing Surgical Skills with AI

Currently, assessment of a surgeon’s skill is done manually by experts, either directly during the operation, or from video footage. This is a time-consuming, not always reproducible and potentially subjective procedure, and there have been attempts to automate it. 

A group of researchers has applied machine learning (ML) algorithms to automate surgical skill assessment in laparoscopic cholecystectomy videos. They developed a method comprising three stages:

1. Training of a Convolutional Neural Network (CNN) to recognise instruments in video frames
2. Tracking these instruments over time and calculating relevant motion metrics
3. Training a linear regression model on those metrics to assess surgical skill.

For the study, a sample of 242 videos was selected, divided into 949 clip applications of surgical gestures (the end of the hepatocystic dissection phase). A panel of surgeons rated the recordings of laparoscopic cholecystectomy.