Evaluation of Quantitative Decision‐Making for Rhythm Management of Atrial Fibrillation Using Tabular Q‐Learning

Background Rhythm management is a complex decision for patients with atrial fibrillation (AF). Although clinical trials have identified subsets of patients who might benefit from a given rhythm-management strategy, for individual patients it is not always clear which strategy is expected to have the...

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Vydáno v:	Journal of the American Heart Association Ročník 12; číslo 9; s. e028483
Hlavní autoři:	Barrett, Christopher D., Suzuki, Yuto, Hussein, Sundos, Garg, Lohit, Tumolo, Alexis, Sandhu, Amneet, West, John J., Zipse, Matthew, Aleong, Ryan, Varosy, Paul, Tzou, Wendy S., Banaei‐Kashani, Farnoush, Rosenberg, Michael A.
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	England John Wiley and Sons Inc 02.05.2023 Wiley
Témata:	Anti-Arrhythmia Agents - therapeutic use Artificial Intelligence atrial fibrillation Atrial Fibrillation - drug therapy Atrial Fibrillation - therapy Electric Countershock Humans Original Research Q‐learning rate control reinforcement learning Retrospective Studies rhythm control atrial fibrillation Q‐learning rate control artificial intelligence reinforcement learning rhythm control unsupervised learning
ISSN:	2047-9980, 2047-9980
On-line přístup:	Získat plný text
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