Blood-Based Biomarkers for Predicting the Risk for Five-Year Incident Coronary Heart Disease in the Framingham Heart Study via Machine Learning

Blood-Based Biomarkers for Predicting the Risk for Five-Year Incident Coronary Heart Disease in the Framingham Heart Study via Machine Learning

An improved approach for predicting the risk for incident coronary heart disease (CHD) could lead to substantial improvements in cardiovascular health. Previously, we have shown that genetic and epigenetic loci could predict CHD status more sensitively than conventional risk factors. Herein, we exam...

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Bibliographic Details
Main Authors: Meeshanthini V. Dogan, Steven R. H. Beach, Ronald L. Simons, Amaury Lendasse, Brandan Penaluna, Robert A. Philibert
Format: Article
Language:English
Published: MDPI AG 2018-12-01
Series:Genes
Subjects:
coronary heart disease
risk prediction
machine learning
epigenetics
genetics
biomarkers
risk factors
Online Access:https://www.mdpi.com/2073-4425/9/12/641

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