Using AI to predict cardiovascular disease

Principal Investigator

Name
yuankai wang

Degrees
Ph.D

Institution
University of Liverpool

Position Title
Student

Email
psywa156@liverpool.ac.uk

About this CDAS Project

Study
NLST (Learn more about this study)

Project ID
NLST-1110

Initial CDAS Request Approval
Aug 8, 2023

Title
Using AI to predict cardiovascular disease

Summary
The project aims to develop a predictive model for estimating the Coronary Artery Calcium (CAC) score using Computed Tomography (CT) images.
The CAC score is a well-established indicator of coronary artery disease and is widely used in cardiovascular risk assessment. The ability to accurately predict the CAC score from CT images can significantly aid in early detection and prevention of heart diseases, leading to improved patient outcomes and reduced healthcare costs.

Aims

The primary objective of this project is to leverage state-of-the-art machine learning techniques and image analysis algorithms to create a robust and accurate model for predicting the CAC score from CT images.

Collaborators

University of Liverpool. Liverpool Heart and Chest Hospital