NIH R01 · 2025
Opportunistic Screening for ASCVD using a Multimodal Deep Learning Risk Prediction Model
PROJECT SUMMARY Atherosclerotic cardiovascular disease (ASCVD), such as stroke and heart attack, is the leading cause of morbidity and mortality globally, responsible for approximately 19 million deaths annually. Risk assessment is the cornerstone for primary prevention of ASCVD. Pooled Cohort Equations (PCE) are currently used to guide risk assessment and tailor preventive therapies. However, these and other risk prediction tools remain imperfect and have significant limitations including being static and based on a small number of simple clinical variables as well as having poor performance across diverse populations. Moreover, they do not incorporate imaging that may contain known…
From the public funding record at NIH RePORTER. Describes the funded project, not the reviews below.