The Use of Synthetic Electronic Health Record Data and Deep Learning to Improve Timing of High-Risk Heart Failure Surgical Intervention by Predicting Proximity to Catastrophic Decompensation

Objective: Although many clinical metrics are associated with proximity to decompensation in heart failure (HF), none are individually accurate enough to risk-stratify HF patients on a patient-by-patient basis. The dire consequences of this inaccuracy in risk stratification have profoundly lowered t...

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Detalles Bibliográficos
Autores principales: Guo, Aixia, Foraker, Randi E., MacGregor, Robert M., Masood, Faraz M., Cupps, Brian P., Pasque, Michael K.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2020
Materias:
Digital Health
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8521851/
https://www.ncbi.nlm.nih.gov/pubmed/34713050
http://dx.doi.org/10.3389/fdgth.2020.576945

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8521851/
https://www.ncbi.nlm.nih.gov/pubmed/34713050
http://dx.doi.org/10.3389/fdgth.2020.576945

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