Using machine learning to predict anticoagulation control in atrial fibrillation: A UK Clinical Practice Research Datalink study
Objective: 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. Methods: This was a retrospective cohort study of adult patients (≥18 years) between 2007 and 2016...
Main Authors: | Jason Gordon, Max Norman, Michael Hurst, Thomas Mason, Carissa Dickerson, Belinda Sandler, Kevin G. Pollock, Usman Farooqui, Lara Groves, Carmen Tsang, David Clifton, Ameet Bakhai, Nathan R. Hill |
---|---|
Format: | Article |
Language: | English |
Published: |
Elsevier
2021-01-01
|
Series: | Informatics in Medicine Unlocked |
Subjects: | |
Online Access: | http://www.sciencedirect.com/science/article/pii/S2352914821001726 |
Similar Items
-
Are patients on oral anticoagulation therapy aware of its effects? A cross-sectional study from Karachi, Pakistan
by: Ibrahim Zahid, et al.
Published: (2020-06-01) -
ANTICOAGULATION CONTROL AMONG PATIENTS WITH ATRIAL FIBRILLATION
by: Amer Rauf, et al.
Published: (2020-12-01) -
An unusual complication during anticoagulant therapy
by: M. T. Vatutin, et al.
Published: (2015-10-01) -
Beyond warfarin: The advent of new oral anticoagulants
by: Sandeep T Laroia, et al.
Published: (2015-10-01) -
Potential factors affecting the anticoagulation control in patients treated with warfarin: Results WARFARIN-TR study
by: Salih Kilic, et al.
Published: (2018-01-01)