Machine learning approaches to predict the 1-year-after-initial-AMI survival of elderly patients.

ABSTRACT:

Background

While multiple randomized controlled trials (RCTs) are available, their results may not be generalizable to older, unhealthier or less-adherent patients. Observational data can be used to predict outcomes and evaluate treatments; however, exactly which strategy should be used to analyze the outcomes of treatment using observational data is currently unclear. This study aimed to determine the most accurate machine learning technique to predict 1-year-after-initial-acute-myocardial-infarction (AMI) survival of elderly patients and to identify the association of angiotensin-converting- enzyme inhibitors and angiotensin-receptor blockers (ACEi/ARBs) with survival.

Methods

We built a cohort of 124,031 Medicare beneficiaries who experienced an AMI in 2007 or 2008. For a

SUBMITTER: Lee J 

PROVIDER: S-EPMC9052482 | biostudies-literature | 2022 Apr

REPOSITORIES: biostudies-literature