Deep Learning on Electrocardiograms for Prediction of In-hospital Intradialytic Hypotension in Patients with ESKD

Intradialytic hypotension is common in patients who are on hemodialysis. We applied deep learning techniques to ECGs to predict patients at risk of IDH. The performance of the model was good with an AUC of 0.763 and AUPRC of 0.35.

Detalles Bibliográficos
Autores principales: Vaid, Akhil, Takkavatakarn, Kullaya, Divers, Jasmin, Charytan, David M., Chan, Lili, Nadkarni, Girish N.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Society of Nephrology 2023
Materias:
Brief Communication
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10547223/
https://www.ncbi.nlm.nih.gov/pubmed/37418626
http://dx.doi.org/10.34067/KID.0000000000000208
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author Vaid, Akhil
Takkavatakarn, Kullaya
Divers, Jasmin
Charytan, David M.
Chan, Lili
Nadkarni, Girish N.
author_facet Vaid, Akhil
Takkavatakarn, Kullaya
Divers, Jasmin
Charytan, David M.
Chan, Lili
Nadkarni, Girish N.
author_sort Vaid, Akhil
collection PubMed
description Intradialytic hypotension is common in patients who are on hemodialysis. We applied deep learning techniques to ECGs to predict patients at risk of IDH. The performance of the model was good with an AUC of 0.763 and AUPRC of 0.35.
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spelling pubmed-105472232023-10-04 Deep Learning on Electrocardiograms for Prediction of In-hospital Intradialytic Hypotension in Patients with ESKD Vaid, Akhil Takkavatakarn, Kullaya Divers, Jasmin Charytan, David M. Chan, Lili Nadkarni, Girish N. Kidney360 Brief Communication Intradialytic hypotension is common in patients who are on hemodialysis. We applied deep learning techniques to ECGs to predict patients at risk of IDH. The performance of the model was good with an AUC of 0.763 and AUPRC of 0.35. American Society of Nephrology 2023-07-07 /pmc/articles/PMC10547223/ /pubmed/37418626 http://dx.doi.org/10.34067/KID.0000000000000208 Text en Copyright © 2023 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the American Society of Nephrology https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution-Non Commercial-No Derivatives License 4.0 (CCBY-NC-ND) (https://creativecommons.org/licenses/by-nc-nd/4.0/) , where it is permissible to download and share the work provided it is properly cited. The work cannot be changed in any way or used commercially without permission from the journal.
spellingShingle Brief Communication
Vaid, Akhil
Takkavatakarn, Kullaya
Divers, Jasmin
Charytan, David M.
Chan, Lili
Nadkarni, Girish N.
Deep Learning on Electrocardiograms for Prediction of In-hospital Intradialytic Hypotension in Patients with ESKD
title Deep Learning on Electrocardiograms for Prediction of In-hospital Intradialytic Hypotension in Patients with ESKD
title_full Deep Learning on Electrocardiograms for Prediction of In-hospital Intradialytic Hypotension in Patients with ESKD
title_fullStr Deep Learning on Electrocardiograms for Prediction of In-hospital Intradialytic Hypotension in Patients with ESKD
title_full_unstemmed Deep Learning on Electrocardiograms for Prediction of In-hospital Intradialytic Hypotension in Patients with ESKD
title_short Deep Learning on Electrocardiograms for Prediction of In-hospital Intradialytic Hypotension in Patients with ESKD
title_sort deep learning on electrocardiograms for prediction of in-hospital intradialytic hypotension in patients with eskd
topic Brief Communication
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10547223/
https://www.ncbi.nlm.nih.gov/pubmed/37418626
http://dx.doi.org/10.34067/KID.0000000000000208
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