Artificially intelligent proteomics improves cardiovascular risk assessment

Abstract

Cardiovascular disease (CVD) diagnosis, risk stratification, and treatment have improved significantly since the landmark Framingham Heart Study first defined key risk factors 50 years ago [1]. However, widespread use of indices such as the Framingham Risk Score (FRS) to guide patient management has not altered CVD status as the leading cause of mortality worldwide (still contributing to 1 in every 3 deaths in developed countries). This high burden of CVD persists due to the substantial amount of residual disease despite the use of anti-lipid, anti-hypertensive and anti-diabetic drugs for primary and secondary preventions.