Artificial intelligence algorithm for predicting mortality of patients with acute heart failure

AIMS: This study aimed to develop and validate deep-learning-based artificial intelligence algorithm for predicting mortality of AHF (DAHF). METHODS AND RESULTS: 12,654 dataset from 2165 patients with AHF in two hospitals were used as train data for DAHF development, and 4759 dataset from 4759 patie...

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Detalles Bibliográficos
Autores principales: Kwon, Joon-myoung, Kim, Kyung-Hee, Jeon, Ki-Hyun, Lee, Sang Eun, Lee, Hae-Young, Cho, Hyun-Jai, Choi, Jin Oh, Jeon, Eun-Seok, Kim, Min-Seok, Kim, Jae-Joong, Hwang, Kyung-Kuk, Chae, Shung Chull, Baek, Sang Hong, Kang, Seok-Min, Choi, Dong-Ju, Yoo, Byung-Su, Kim, Kye Hun, Park, Hyun-Young, Cho, Myeong-Chan, Oh, Byung-Hee
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2019
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6613702/
https://www.ncbi.nlm.nih.gov/pubmed/31283783
http://dx.doi.org/10.1371/journal.pone.0219302

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6613702/
https://www.ncbi.nlm.nih.gov/pubmed/31283783
http://dx.doi.org/10.1371/journal.pone.0219302

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