Stephen John Payne

This paper introduces a computational pipeline to predict brain swelling after stroke using a mathematical model and deep neural network, achieving an AUC of 0.7 in predicting 3-month outcomes.

This paper develops an AI-assisted in-silico trial to optimize osmotherapy protocols for ischaemic stroke by predicting intracranial pressure and personalizing treatment based on patient-specific data.

This study quantifies oxygen transport parameters in the human brain using a multi-scale model and validates them against experimental data and anatomical structures.

This paper models how cerebral microthrombi affect tissue oxygenation and cell death using computational simulations and a hypoxia-based cell death model.

The paper develops an in-silico model to simulate micro-emboli effects on brain microcirculation after thrombectomy, finding capillary beds are more susceptible to occlusion than arterioles.