Causal insights from clinical information in radiology: Enhancing future multimodal AI development.
Journal:
Computer methods and programs in biomedicine
Published Date:
Aug 1, 2025
Abstract
PURPOSE: This study investigates the causal mechanisms underlying radiology report generation by analyzing how clinical information and prior imaging examinations contribute to annotation shifts. We systematically estimate why and how biases manifest, providing insights into the data generation process that influences radiology reporting.