Clara E Jones

This paper introduces a population-level emulator for Bayesian calibration of cardiac digital twins, reducing calibration time from 15 hours to under a minute per patient.

This paper presents a computational model of hemodynamics during atrial fibrillation that fits clinical data from 17 patients, achieving high accuracy in blood pressure and ejection fraction measurements.

This study develops a computational framework combining biophysics and machine learning to predict cardiac growth probability, validated using canine MVR data.