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ABSTRACT: Background and objective
With the wide application of electronic medical record systems in hospitals, massive medical data are available. This type of medical data has the characteristics of heterogeneity and multi-dimensionality. Traditional statistical methods cannot fully extract and use such data, but with their non-linear and cross-learning modes, machine-learning (ML) algorithms based on artificial intelligence can address these shortcomings. To explore the application of ML algorithms in the cardiovascular field, we retrieved and reviewed relevant articles published in the last 6 years and found that ML is practical and accurate in the auxiliary diagnosis of cardiovascular diseases. Thus, this article reviewed the research progress of ML in cardiovascular disease.Methods
SUBMITTER: Chen L
PROVIDER: S-EPMC9201135 | biostudies-literature | 2022 May
REPOSITORIES: biostudies-literature