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...
Main Authors: | Aixia Guo, Randi E. Foraker, Robert M. MacGregor, Faraz M. Masood, Brian P. Cupps, Michael K. Pasque |
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Format: | Article |
Language: | English |
Published: |
Frontiers Media S.A.
2020-12-01
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Series: | Frontiers in Digital Health |
Subjects: | |
Online Access: | https://www.frontiersin.org/articles/10.3389/fdgth.2020.576945/full |
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