Artificial Intelligence for Evidence Generation and Synthesis
Moderator
Beate Jahn, PhD, UMIT – University for Health Sciences, Medical Informatics and Technology, Hall i.T., Austria
Artificial intelligence is rapidly transforming the way evidence is identified, synthesized, and interpreted in health economics and outcomes research. This session showcases innovative applications of AI to systematic literature reviews, evidence identification, and evidence synthesis workflows. Presentations will highlight methodological advances that improve efficiency, reproducibility, and transparency while maintaining scientific rigor. Together, these studies demonstrate how AI can support high-quality evidence generation for health technology assessment and healthcare decision-making.