Artificial intelligence assessment for early detection and prediction of renal impairment using electrocardiography

PURPOSE: Although renal failure is a major healthcare burden globally and the cornerstone for preventing its irreversible progression is an early diagnosis, an adequate and noninvasive tool to screen renal impairment (RI) reliably and economically does not exist. We developed an interpretable deep l...

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Detalles Bibliográficos
Autores principales: Kwon, Joon-myoung, Kim, Kyung-Hee, Jo, Yong-Yeon, Jung, Min-Seung, Cho, Yong-Hyeon, Shin, Jae-Hyun, Lee, Yoon-Ji, Ban, Jang-Hyeon, Lee, Soo Youn, Park, Jinsik, Oh, Byung-Hee
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Netherlands 2022
Materias:
Nephrology - Original Paper
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9463260/
https://www.ncbi.nlm.nih.gov/pubmed/35403974
http://dx.doi.org/10.1007/s11255-022-03165-w

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9463260/
https://www.ncbi.nlm.nih.gov/pubmed/35403974
http://dx.doi.org/10.1007/s11255-022-03165-w

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