Improving dynamic stroke risk prediction in non-anticoagulated patients with and without atrial fibrillation: comparing common clinical risk scores and machine learning algorithms — Professor Gregory Lip (2021) | RDL Network
Improving dynamic stroke risk prediction in non-anticoagulated patients with and without atrial fibrillation: comparing common clinical risk scores and machine learning algorithms
In this large cohort of newly diagnosed non-anticoagulated AF/non-AF patients, large improvements in stroke risk prediction can be shown with cardiovascular/non-cardiovascular multi-morbid index and a machine learning approach accounting for dynamic changes in risk factors.
Amaya García-Fernández, Vanessa Roldán, José Miguel Rivera‐Caravaca, Diana Hernández‐Romero, Mariano Valdés, Vicente Vicente, Professor Gregory Lip, Francisco Marı́n
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