AUGUR-AIM: Clinical validation of an artificial intelligence indocyanine green fluorescence angiography expert representer.

ABSTRACT:

Aim

Recent randomized controlled trials and meta-analyses have demonstrated a reduction in the anastomotic leak rate when indocyanine green fluorescence angiography (ICGFA) is used versus when it is not in colorectal resections. We have previously demonstrated that an artificial intelligence (AI) model, AUGUR-AI, can digitally represent in real time where experienced ICGFA users would place their surgical stapler based on their interpretation of the fluorescence imagery. The aim of this study, called AUGUR-AIM, is to validate this method across multiple clinical sites with regard to generalizability, usability and accuracy while generating new algorithms for testing and determining the optimal mode of deployment for the software device.

Method

This is a prospective, observat

SUBMITTER: Mc Entee PD 

PROVIDER: S-EPMC11997639 | biostudies-literature | 2025 Apr

REPOSITORIES: biostudies-literature