Central Illustration: Machine Learning-Driven Precision Cardiology

Multiple sources of heterogeneous data, including experimental evidence, bioinformatics databases, lifestyle measurements, electronic health records, environmental influences, and biobank findings, can be incorporated together using machine learning algorithms to identify causal disease networks, stratify patients, and ultimately predict more efficacious therapies.