Machine learning for outcome prediction in patients with non-valvular atrial fibrillation from the GLORIA-AF registry

Abstract Clinical risk scores that predict outcomes in patients with atrial fibrillation (AF) have modest predictive value. Machine learning (ML) may achieve greater results when predicting adverse outcomes in patients with recently diagnosed AF. Several ML models were tested and compared with curre...

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Principais autores:	Martha Joddrell, Wahbi El-Bouri, Stephanie L. Harrison, Menno V. Huisman, Gregory Y. H. Lip, Yalin Zheng, GLORIA-AFinvestigators
פורמט:	Artigo
שפה:	Inglês
יצא לאור:	Nature Portfolio 2024-11-01
סדרה:	Scientific Reports
גישה מקוונת:	https://doi.org/10.1038/s41598-024-78120-z
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