Artificial intelligence (AI) in pharmacovigilance: A systematic review on predicting adverse drug reactions (ADR) in hospitalized patients

Viola Savy Dsouza, Lada Leyens, Jestina Rachel Kurian, Angela Brand, Helmut Brand

The findings highlight the need for multifactorial models that integrate diverse predictors to improve the performance and reliability of ML-based ADR prediction. Addressing these limitations through rigorous model development and validation processes could enhance the clinical applicability of AI-driven pharmacovigilance, ultimately advancing patient safety and healthcare outcomes.