Refining Echocardiographic Surveillance of Aortic Stenosis Using Machine Learning: Toward Personalized and Sustainable Follow-Up Schemes

JACC Cardiovasc Imaging. 2023 Jun;16(6):745-748. doi: 10.1016/j.jcmg.2023.01.019. Epub 2023 Mar 23.

Authors

Attila Kovács¹, Márton Tokodi²

Affiliations

¹ Heart and Vascular Center, Semmelweis University, Budapest, Hungary. Electronic address: attila.kovacs@semmelweis.hu.
² Heart and Vascular Center, Semmelweis University, Budapest, Hungary; Division of Cardiovascular Diseases and Hypertension, Rutgers Robert Wood Johnson Medical School, New Brunswick, New Jersey, USA.

PMID: 37038877
DOI: 10.1016/j.jcmg.2023.01.019

No abstract available

Keywords: aortic stenosis; echocardiography; follow-up; machine learning; personalized medicine.

Publication types

Editorial
Research Support, Non-U.S. Gov't
Comment

MeSH terms

Aortic Valve / diagnostic imaging
Aortic Valve Stenosis* / diagnostic imaging
Echocardiography*
Follow-Up Studies
Humans
Machine Learning
Predictive Value of Tests