Intelligent monitoring to predict atrial fibrillation (NOTE-AF): clinical study 1 for the 'Health virtual twins for the personalised management of stroke related to atrial fibrillation (TARGET)' project - a protocol for a prospective cohort analysis.

ABSTRACT:

Introduction

Atrial Fibrillation (AF) is the most common arrhythmia worldwide affecting an estimated 5% of people over the age of 65 and is a leading cause of stroke and heart failure. Identification of patients at risk allows preventative measures and treatment before these complications occur. Conventional risk prediction models are static, do not have flexibility to incorporate dynamic risk factors and possess only modest predictive value. Artificial intelligence and machine learning-powered health virtual twin technology offer transformative methods for risk prediction and guiding clinical decisions.

Methods and analysis

In this prospective observational study, 1200 patients will be recruited in two tertiary centres. Patients hospitalised with acute illnesses (sepsis, he

SUBMITTER: Essa H 

PROVIDER: S-EPMC12766758 | biostudies-literature | 2026 Jan

REPOSITORIES: biostudies-literature