| Autor: |
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 |
| Jazyk: |
angličtina |
| Rok vydání: |
2021 |
| Předmět: |
|
| Zdroj: |
Informatics in Medicine Unlocked, Vol 25, Iss , Pp 100688- (2021) |
| Druh dokumentu: |
article |
| ISSN: |
2352-9148 |
| DOI: |
10.1016/j.imu.2021.100688 |
| Popis: |
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 using linked primary and secondary care data (Clinical Practice Research Datalink GOLD and Hospital Episode Statistics). Various ML techniques were explored to predict suboptimal anticoagulation control, defined as time in therapeutic range (TTR) 80 years and |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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