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Electrocardiogram-Based Heart Age Estimation by a Deep Learning Model Provides More Information on the Incidence of Cardiovascular Disorders

ObjectiveThe biological age progression of the heart varies from person to person. We developed a deep learning model (DLM) to predict the biological age via ECG to explore its contribution to future cardiovascular diseases (CVDs).MethodsThere were 71,741 cases ranging from 20 to 80 years old recrui...

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Principais autores: Chiao-Hsiang Chang, Chin-Sheng Lin, Yu-Sheng Luo, Yung-Tsai Lee, Chin Lin
Formato: Artigo
Idioma:Inglês
Publicado em: Frontiers Media S.A. 2022-02-01
coleção:Frontiers in Cardiovascular Medicine
Assuntos:
artificial intelligence
electrocardiography
deep learning
cardiovascular diseases
chronological age
Acesso em linha:https://www.frontiersin.org/articles/10.3389/fcvm.2022.754909/full
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