Tool-tissue force segmentation and pattern recognition for evaluating neurosurgical performance.

ABSTRACT: Surgical data quantification and comprehension expose subtle patterns in tasks and performance. Enabling surgical devices with artificial intelligence provides surgeons with personalized and objective performance evaluation: a virtual surgical assist. Here we present machine learning models developed for analyzing surgical finesse using tool-tissue interaction force data in surgical dissection obtained from a sensorized bipolar forceps. Data modeling was performed using 50 neurosurgery procedures that involved elective surgical treatment for various intracranial pathologies. The data collection was conducted by 13 surgeons of varying experience levels using sensorized bipolar forceps, SmartForceps System. The machine learning algorithm constituted design and implementation for three primar

SUBMITTER: Baghdadi A 

PROVIDER: S-EPMC10264433 | biostudies-literature | 2023 Jun

REPOSITORIES: biostudies-literature