Artificial intelligence for detecting electrolyte imbalance using electrocardiography

INTRODUCTION: The detection and monitoring of electrolyte imbalance is essential for appropriate management of many metabolic diseases; however, there is no tool that detects such imbalances reliably and noninvasively. In this study, we developed a deep learning model (DLM) using electrocardiography...

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Detalles Bibliográficos
Autores principales: Kwon, Joon‐myoung, Jung, Min‐Seung, Kim, Kyung‐Hee, Jo, Yong‐Yeon, Shin, Jae‐Hyun, Cho, Yong‐Hyeon, Lee, Yoon‐Ji, Ban, Jang‐Hyeon, Jeon, Ki‐Hyun, Lee, Soo Youn, Park, Jinsik, Oh, Byung‐Hee
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2021
Materias:
New Technologies
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8164149/
https://www.ncbi.nlm.nih.gov/pubmed/33719135
http://dx.doi.org/10.1111/anec.12839

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8164149/
https://www.ncbi.nlm.nih.gov/pubmed/33719135
http://dx.doi.org/10.1111/anec.12839

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