An Explainable Artificial Intelligence Approach for Discovering Social Determinants of Health and Risk Interactions for Stroke in Patients With Atrial Fibrillation - 25/07/23
Doi : 10.1016/j.amjcard.2023.05.064
Raquel M. Zimmerman, BA a, Edgar J. Hernandez, PhD b, W. Scott Watkins, MS b, Nathan Blue, MD c, Martin Tristani-Firouzi, MD d, Mark Yandell, PhD b, Benjamin A. Steinberg, MD, MHS e, ⁎ 
a Department of Biomedical Informatics, University of Utah, Utah
b Utah Center for Genetic Discovery, Department of Human Genetics, University of Utah, Utah
c Department of Obstetrics and Gynecology, University of Utah, Utah
d Department of Pediatrics, University of Utah, Utah
e Division of Cardiology, Department of Medicine, University of Utah, Salt Lake City, Utah
⁎Corresponding author: Tel: 801-585-7676; fax: 801-581-7735.
| Dr. Steinberg reports resesarch support from the National Heart, Lung, And Blood Institute of the National Institutes of Health under Award Number K23HL143156; research support from AHA/PCORI, Abbott, Cardiva, Sanofi, and AltaThera; and consulting to Sanofi, InCarda, Milestone, Pfizer, and AltaThera. No other relevant disclosures were reported by the authors. |
© 2023
Elsevier Inc. Tous droits réservés.
Vol 201
P. 224-226 - août 2023 Retour au numéro
Article précédent
- Atrial Cardiopathy: Redefining Stroke Risk Beyond Atrial Fibrillation
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