Progress in the application of deep learning in the auxiliary diagnosis and prognostic evaluation of left ventricular hypertrophy
- VernacularTitle:深度学习在左心室肥厚辅助诊断和预后评估中的应用进展
- Author:
Hongyang XU
1
;
Peng QIU
1
;
Hui CAO
1
;
Junzhong ZHANG
2
;
Zhiming MA
1
Author Information
1. School of Medical Information Engineering, Shandong University of Traditional Chinese Medicine, Jinan, 250355, P. R. China
2. First Clinical Medical College, Shandong University of Traditional Chinese Medicine, Jinan, 250355, P. R. China
- Publication Type:Journal Article
- Keywords:
Deep learning;
left ventricular hypertrophy;
echocardiography;
cardiac magnetic resonance imaging;
electrocardiogram;
prognosis;
review
- From:
Chinese Journal of Clinical Thoracic and Cardiovascular Surgery
2025;32(10):1495-1503
- CountryChina
- Language:Chinese
-
Abstract:
As an intermediate phenotype for multiple cardiovascular diseases, left ventricular hypertrophy (LVH) benefits from early diagnosis, which allows for timely intervention to prevent worsening of the condition, mitigate severe complications like heart failure and arrhythmias, and consequently improve patient outcomes. Preliminary advances have been made using deep learning for the early diagnosis and identification of etiology in LVH. This paper reviews the pathophysiology, causes, and diagnostic standards for LVH, discusses the strengths and weaknesses of applying deep learning to diagnostic tools such as echocardiography, cardiac magnetic resonance imaging, and electrocardiogram, examines its use in prognostic evaluation, and concludes by summarizing current achievements and suggesting future research avenues.
