Get 20M+ Full-Text Papers For Less Than $1.50/day. Start a 14-Day Trial for You or Your Team.

Learn More →

Artificial Intelligence Pipeline for Risk Prediction in Cardiovascular Imaging

Artificial Intelligence Pipeline for Risk Prediction in Cardiovascular Imaging Circulation: Cardiovascular Imaging EDITORIAL Artificial Intelligence Pipeline for Risk Prediction in Cardiovascular Imaging See Article by Kay et al Karen G. Ordovas, MD, MAS Youngho Seo, PhD ith the advent of modern artificial intelligence (AI), physicians and sci- entists have the opportunity to develop specific tools that can detect Wphenotypic features in the heart that would otherwise remain unrecog- nized. This ability to use large imaging datasets to further risk stratify patients for cardiovascular events and potentially modify outcomes is a very exciting new fron- tier in medicine. When developed under rigorous scientific methodology and vali- dated with appropriate methods, AI models have the potential to aid our under- standing of heart disease and could be used to inform risk modification strategies. Noninvasive imaging identification of left ventricular hypertrophy (LVH) is an important imaging biomarker as it is associated with increased risk of cardiovascu- 3,4 lar events and death. More importantly, LVH is a modifiable risk factor, as the risk 5,6 of events decreases when LVH resolves or improves. Unless patients undergo a dedicated cardiac imaging study, it is unlikely that presence and degree of LVH will be identified in asymptomatic individuals. In the current issue of the journal, http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Circulation: Cardiovascular Imaging Wolters Kluwer Health

Artificial Intelligence Pipeline for Risk Prediction in Cardiovascular Imaging

Loading next page...
 
/lp/wolters-kluwer-health/artificial-intelligence-pipeline-for-risk-prediction-in-cardiovascular-Om1n5i3ZIz

References

References for this paper are not available at this time. We will be adding them shortly, thank you for your patience.

Publisher
Wolters Kluwer Health
Copyright
© 2020 American Heart Association, Inc.
ISSN
1941-9651
eISSN
1942-0080
DOI
10.1161/CIRCIMAGING.120.010427
Publisher site
See Article on Publisher Site

Abstract

Circulation: Cardiovascular Imaging EDITORIAL Artificial Intelligence Pipeline for Risk Prediction in Cardiovascular Imaging See Article by Kay et al Karen G. Ordovas, MD, MAS Youngho Seo, PhD ith the advent of modern artificial intelligence (AI), physicians and sci- entists have the opportunity to develop specific tools that can detect Wphenotypic features in the heart that would otherwise remain unrecog- nized. This ability to use large imaging datasets to further risk stratify patients for cardiovascular events and potentially modify outcomes is a very exciting new fron- tier in medicine. When developed under rigorous scientific methodology and vali- dated with appropriate methods, AI models have the potential to aid our under- standing of heart disease and could be used to inform risk modification strategies. Noninvasive imaging identification of left ventricular hypertrophy (LVH) is an important imaging biomarker as it is associated with increased risk of cardiovascu- 3,4 lar events and death. More importantly, LVH is a modifiable risk factor, as the risk 5,6 of events decreases when LVH resolves or improves. Unless patients undergo a dedicated cardiac imaging study, it is unlikely that presence and degree of LVH will be identified in asymptomatic individuals. In the current issue of the journal,

Journal

Circulation: Cardiovascular ImagingWolters Kluwer Health

Published: Feb 1, 2020

There are no references for this article.