Cargando…
Predicting patient-level new-onset atrial fibrillation from population-based nationwide electronic health records: protocol of FIND-AF for developing a precision medicine prediction model using artificial intelligence
INTRODUCTION: Atrial fibrillation (AF) is a major cardiovascular health problem: it is common, chronic and incurs substantial healthcare expenditure because of stroke. Oral anticoagulation reduces the risk of thromboembolic stroke in those at higher risk; but for a number of patients, stroke is the...
Autores principales: | Nadarajah, Ramesh, Wu, Jianhua, Frangi, Alejandro F, Hogg, David, Cowan, Campbell, Gale, Chris |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BMJ Publishing Group
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8565546/ https://www.ncbi.nlm.nih.gov/pubmed/34728455 http://dx.doi.org/10.1136/bmjopen-2021-052887 |
Ejemplares similares
-
What is next for screening for undiagnosed atrial fibrillation? Artificial intelligence may hold the key
por: Nadarajah, Ramesh, et al.
Publicado: (2021) -
Future Innovations in Novel Detection for Atrial Fibrillation (FIND-AF): pilot study of an electronic health record machine learning algorithm-guided intervention to identify undiagnosed atrial fibrillation
por: Nadarajah, Ramesh, et al.
Publicado: (2023) -
Prediction of incident atrial fibrillation in community-based electronic health records: a systematic review with meta-analysis
por: Nadarajah, Ramesh, et al.
Publicado: (2022) -
Prediction of short-term atrial fibrillation risk using primary care electronic health records
por: Nadarajah, Ramesh, et al.
Publicado: (2023) -
GARFIELD-AF model for prediction of stroke and major bleeding in atrial fibrillation: a Danish nationwide validation study
por: Dalgaard, Frederik, et al.
Publicado: (2019)