Development and External Validation of a Deep Learning Algorithm for Prognostication of Cardiovascular Outcomes

BACKGROUND AND OBJECTIVES: We aim to explore the additional discriminative accuracy of a deep learning (DL) algorithm using repeated-measures data for identifying people at high risk for cardiovascular disease (CVD), compared to Cox hazard regression. METHODS: Two CVD prediction models were develope...

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Detalles Bibliográficos
Autores principales: Cho, In-Jeong, Sung, Ji Min, Kim, Hyeon Chang, Lee, Sang-Eun, Chae, Myeong-Hun, Kavousi, Maryam, Rueda-Ochoa, Oscar L., Ikram, M. Arfan, Franco, Oscar H., Min, James K, Chang, Hyuk-Jae
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Korean Society of Cardiology 2019
Materias:
Original Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6923233/
https://www.ncbi.nlm.nih.gov/pubmed/31456363
http://dx.doi.org/10.4070/kcj.2019.0105

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6923233/
https://www.ncbi.nlm.nih.gov/pubmed/31456363
http://dx.doi.org/10.4070/kcj.2019.0105

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