Cost-Effectiveness of Artificial Intelligence-Enabled Electrocardiograms for Early Detection of Low Ejection Fraction: A Secondary Analysis of the Electrocardiogram Artificial Intelligence-Guided Screening for Low Ejection Fraction Trial
Objective: To investigate the cost-effectiveness of using artificial intelligence (AI) to screen for low ejection fraction (EF) in routine clinical practice using a pragmatic randomized controlled trial (RCT). Patients and Methods: In a post hoc analysis of the electrocardiogram (ECG) AI-guided scre...
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| Main Authors: | Viengneesee Thao, PhD, MS, Ye Zhu, MD, MPH, PhD, Andrew S. Tseng, MD, MPH, Jonathan W. Inselman, MS, Bijan J. Borah, PhD, Rozalina G. McCoy, MD, MS, Zachi I. Attia, PhD, Francisco Lopez-Jimenez, MD, MBA, Patricia A. Pellikka, MD, David R. Rushlow, MD, MBOE, Paul A. Friedman, MD, Peter A. Noseworthy, MD, MBA, Xiaoxi Yao, MPH, MS, PhD |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2024-12-01
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| Series: | Mayo Clinic Proceedings: Digital Health |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2949761224001044 |
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