Development of an AI-driven digital assistance system for real-time safety evaluation and quality control in laparoscopic liver surgery.

ABSTRACT:

Background

By performing AI-driven workflow analysis, intelligent surgical systems can provide real-time intraoperative quality control and alerts. We have upgraded an Intelligent Surgical Assistant (ISA) through integrating a redesigned hierarchical recognition algorithm, an expanded surgical dataset, and an optimized real-time intraoperative feedback framework.

Objective

We aimed to assess the accuracy of the ISA in real-time instrument tracking, organ segmentation, and phase classification during laparoscopic hemi-hepatectomy.

Methods

In this retrospective multi-center analysis, a total of 142861 annotated frames were collected from 403 laparoscopic hemi-hepatectomy videos across 4 centers to build a comprehensive database of surgical video annotations. Each frame

SUBMITTER: Peng ZY 

PROVIDER: S-EPMC12541588 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature