Do artificial intelligence-based electrocardiogram (AI-ECG) algorithms accurately detect heart failure with preserved ejection fraction (HFpEF)?
This systematic review and meta-analysis aims to evaluate the diagnostic accuracy of AI-ECG algorithms for detecting HFpEF.
Background: Heart failure with preserved ejection fraction (HFpEF) is a highly prevalent syndrome associated with substantial morbidity and mortality. Accurate diagnosis is often challenging and costly. Recently, artificial intelligence-based electrocardiogram (AI-ECG) algorithms have emerged to make the diagnosis of HFpEF less expensive and more accessible. However, there is a lack of data regarding their accuracy. Objective: We aimed to conduct a systematic review and meta-analysis to evaluate the diagnostic performance of AI-ECG algorithms in detecting HFpEF. Methods: We searched ...
David et al. (Thu,) studied this question.