Summary

Explores methods to explain predictions of machine learning classifiers assessing adverse event report seriousness for regulatory compliance in pharmacovigilance. Investigates model differences, regulatory criteria alignment, and automatic feature patterns. Finds Kendall correlations between models exist but differ per reporter group.