Automation of surgical skill assessment using a three-stage machine learning algorithm.

ABSTRACT: Surgical skills are associated with clinical outcomes. To improve surgical skills and thereby reduce adverse outcomes, continuous surgical training and feedback is required. Currently, assessment of surgical skills is a manual and time-consuming process which 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 skill

SUBMITTER: Lavanchy JL 

PROVIDER: S-EPMC7933408 | biostudies-literature | 2021 Mar

REPOSITORIES: biostudies-literature