Using machine learning to predict anticoagulation control in atrial fibrillation: a UK Clinical Practice Research Datalink study
<strong>Objective<br></strong> To investigate the predictive performance of machine learning (ML) algorithms for estimating anticoagulation control in patients with atrial fibrillation (AF) who are treated with warfarin. <br><strong> Methods<br></strong> Thi...
Κύριοι συγγραφείς: | Gordon, J, Norman, M, Hurst, M, Mason, T, Dickerson, C, Sandler, B, Pollock, KG, Farooqui, U, Groves, L, Tsang, C, Clifton, D, Bakhai, A, Hill, NR |
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Μορφή: | Journal article |
Γλώσσα: | English |
Έκδοση: |
Elsevier
2021
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Παρόμοια τεκμήρια
Παρόμοια τεκμήρια
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Using machine learning to predict anticoagulation control in atrial fibrillation: A UK Clinical Practice Research Datalink study
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Identification of undiagnosed atrial fibrillation using a machine learning risk prediction algorithm and diagnostic testing (PULsE-AI) in primary care: cost-effectiveness of a screening strategy evaluated in a randomized controlled trial in England
ανά: Hill, NR, κ.ά.
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Comparison of oral anticoagulants for stroke prevention in atrial fibrillation using the UK clinical practice research Datalink Aurum: A reference trial (ARISTOTLE) emulation study.
ανά: Emma Maud Powell, κ.ά.
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