Analysis of Adverse Events in Anesthesia Using Artificial Intelligence

The interest of health databases in anesthesia is no longer to be demonstrated. The aim of this research was to develop a natural language processing approach to establish a classification of adverse events observed during the perioperative period and to facilitate their analysis: The main objective of the study was to identify what a "naïve" unsupervised model would discover based on Adverse Event (AE) descriptions. Our second goal was to identify apparently unrelated events whose combination could favor the occurrence of an AE