Artificially intelligent proteomics improves cardiovascular risk assessment

• Main Author: Sze, Siu Kwan
• Other Authors: School of Biological Sciences
• Format: Article
• Language: English
• Published: 2019
• Subjects: DRNTU::Science::Biological sciences; Cardiovascular; Risk Assessment
• Online Access: https://hdl.handle.net/10356/98775; http://hdl.handle.net/10220/48570
• Institution: Nanyang Technological University

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.