Demystifying AI for early AF detection : enhancing diagnostic transparency across modalities

Abstract

This article explores using artificial intelligence (AI) to detect atrial fibrillation (AF) early, highlighting its potential to revolutionise cardiology. It reviews numerous studies demonstrating AI’s superior accuracy to traditional methods, particularly in leveraging electrocardiography data from various sources like smart devices and chest radiographs. A key concern addressed is the ‘black box’ nature of some AI algorithms, emphasising the critical need for transparency to build clinician confidence and ensure ethical patient care. It concludes by advocating for policy changes and further research to enhance AI algorithm transparency and integration into clinical practice.