Electrocardiogram-based artificial intelligence for the diagnosis of heart failure: a systematic review and meta-analysis.

ABSTRACT:

Background

The electrocardiogram (ECG) is an inexpensive and easily accessible investigation for the diagnosis of cardiovascular diseases including heart failure (HF). The application of artificial intelligence (AI) has contributed to clinical practice in terms of aiding diagnosis, prognosis, risk stratification and guiding clinical management. The aim of this study is to systematically review and perform a meta-analysis of published studies on the application of AI for HF detection based on the ECG.

Methods

We searched Embase, PubMed and Web of Science databases to identify literature using AI for HF detection based on ECG data. The quality of included studies was assessed using the Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2) criteria. Random-effects mode

SUBMITTER: Li XM 

PROVIDER: S-EPMC9807402 | biostudies-literature | 2022 Dec

REPOSITORIES: biostudies-literature