Explainability, transparency and black box challenges of AI in radiology: impact on patient care in cardiovascular radiology

Abstract The integration of artificial intelligence (AI) in cardiovascular imaging has revolutionized the field, offering significant advancements in diagnostic accuracy and clinical efficiency. However, the complexity and opacity of AI models, particularly those involving machine learning (ML) and deep learning (DL), raise critical legal and ethical concerns due to their "black box" nature. This manuscript addresses these concerns by providing a comprehensive review of AI technologies in cardiovascular imaging, focusing on the challenges and implications of the black box phenomenon. We begin by outlining the foundational concepts of AI, including ML and DL, and their applications in cardiovascular imaging.…