Oral anticoagulant treatment in atrial fibrillation: the AFIRMA real-world study using natural language processing and machine learning.

Journal: Revista clinica espanola

Published Date: Jun 5, 2024

Abstract

INTRODUCTION: Oral anticoagulation (OAC) is key in atrial fibrillation (AF) thromboprophylaxis, but Spain lacks substantial real-world evidence. We aimed to analyze the prevalence, clinical characteristics, and treatment patterns among patients with AF undertaking OAC, using natural language processing (NLP) and machine learning (ML).

Authors

J Cosín-Sales

Servicio de Cardiología, Hospital Arnau de Vilanova, Valencia, Spain. Electronic address: jcosinsales@gmail.com.
M Anguita

Servicio de Cardiología, Hospital Universitario Reina Sofía, Córdoba, Spain.
C Suárez

Servicio de Medicina Interna, Hospital Universitario La Princesa, Madrid, Spain.
C Arias-Cabrales

Savana Research S.L., Madrid, Spain.
L Martínez-Sanchez

Savana Research S.L., Madrid, Spain.
D Arumi

Departamento Médico, Pfizer España, Madrid, Spain.
S Fernández de Cabo

Departamento Médico, Pfizer España, Madrid, Spain.

Keywords

Administration, Oral Aged Aged, 80 and over Anticoagulants Atrial Fibrillation Female Humans Machine Learning Male Middle Aged Natural Language Processing Retrospective Studies Spain

External Resources

View on PubMed Access via DOI PubMed (38849073)

Oral anticoagulant treatment in atrial fibrillation: the AFIRMA real-world study using natural language processing and machine learning.

Abstract

Authors

Keywords

External Resources

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