Author

C. Gale

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Open access Jul 2026

Scalable risk stratification of undiagnosed heart failure using routine health data and its association with imaging phenotypes and outcomes.

FIND-HF is a scalable EHR-based model which has the potential to help rule out undiagnosed HF in low risk cases, whilst high risk cases are associated with more advanced cardiac dysfunction and worse prognosis.

Y. Nakao, R. Nadarajah, F. Shuweihdi et al. · Scientific Reports · 0 citations

Open access Aug 2026

Prediction of Incident Atrial Fibrillation and Association With Outcomes Using Routine Electronic Health Records in a Western Pacific Population.

A supervised machine learning algorithm for AF in a Western Pacific population was derived and demonstrated that higher risk was associated with hospitalisation for other cardio-renal diseases and death.

J. Hsu, C. Hayward, Tobin Joseph et al. · Heart, Lung and Circulation · 0 citations

Open access Jul 2026

Risk-Guided Screening for Atrial Fibrillation Using Electronic Health Records

The EHR-based machine learning model, FIND-AF 2.0, identifies a high-risk subpopulation for AF diagnosis among patients at elevated risk of stroke and could enable scalable, EHR-driven, risk-guided AF screening.

R. Nadarajah, Jianhua Wu, A. Wahab et al. · Circulation · 0 citations