Cardiovascular Event Prediction by Machine Learning: The Multi-Ethnic Study of Atherosclerosis.

ABSTRACT:

Rationale

Machine learning may be useful to characterize cardiovascular risk, predict outcomes, and identify biomarkers in population studies.

Objective

To test the ability of random survival forests, a machine learning technique, to predict 6 cardiovascular outcomes in comparison to standard cardiovascular risk scores.

Methods and results

We included participants from the MESA (Multi-Ethnic Study of Atherosclerosis). Baseline measurements were used to predict cardiovascular outcomes over 12 years of follow-up. MESA was designed to study progression of subclinical disease to cardiovascular events where participants were initially free of cardiovascular disease. All 6814 participants from MESA, aged 45 to 84 years, from 4 ethnicities, and 6 centers across the United St

SUBMITTER: Ambale-Venkatesh B 

PROVIDER: S-EPMC5640485 | biostudies-literature | 2017 Oct

REPOSITORIES: biostudies-literature