@article{42e1e6b7d7ee473abf6b91becf7195e2,
title = "Big Data and ASCVD Risk Prediction: Building a Better Mouse Trap?",
keywords = "biobank, coronary artery disease, electronic health record, machine learning, polygenic risk score, pooled cohort equations, prevention, Humans, Big Data, Coronary Artery Disease, Animals, Atherosclerosis, Mice",
author = "Khurram Nasir and Andrew DeFilippis",
note = "Funding Information: Dr Nasir is funded by NIH grant 1R01HL158976-01, Esperion, Novartis, and the Jerold B. Katz Academy of Translational Research; and is on the advisory board of Amgen, Novartis, Novo Nordisk, and Esperion. Dr DeFilippis is funded by NIH grants 1R01HL158976-01, 1R01ES029846-01, 2U54HL120163, 2R01 ES019217-06, and R01 HL152081.",
year = "2022",
month = mar,
day = "29",
doi = "10.1016/j.jacc.2022.01.020",
language = "English (US)",
volume = "79",
pages = "1167--1169",
journal = "Journal of the American College of Cardiology",
issn = "0735-1097",
publisher = "Elsevier",
number = "12",
}