Research Projects
Here you'll find a summary of our current and future research projects. If you want to get involved with any, either through undergraduate or postgraduate research, or have your own ideas for a project, please get in touch!
Modelling of Non-Invasive Respiratory Support
Creating explainable, mechanistic, digital twins of patients receiving various types of different types non-invasive respiratory support to improve patient care.
Predicting Patient Outcome in Non-Invasive Respiratory Support
Using advanced machine learning methods to predict if patients will succeed or fail when receiving non-invasive respiratory support.
Assessing Risk of Lung Injury in APRV
Utilising digital twins of patients receiving airway pressure release ventilation to assess the risk of lung injury and to optimise the ventilator settings to minimise the risk of lung injury.
Modelling of Flow Control Ventilation for Cardiac Surgery Patients
Extending the work done in randomised clinical trials by using computational modelling to expand the understanding of the differences between flow controlled ventilation and conventional pressure-control ventilation.
Modelling Pharmacological Interventions for Acute Lung Injury
Assessing the impact of pharmacological therapies and its interactions with mechanical ventilatory support in patients with acute lung injury.
Modelling of Blast Lung Injury and Initial Response
Modelling the impacts of blast lung injury and optimising the emergency therapy which can be provided to patients by first responders.
Automating Settings for Mechanical Ventilation
Using reinforcement learning to automate the settings of mechanical ventilation provided to patients in real time.
Physiological Effects of Prone Positioning
Creating mechanistic models and digital twins to improve our understanding of the impact of patient orientation for both invasively ventilated and awake patients with acute respiratory failure.
Mechanical Ventilation during Extracorporeal Membrane Oxygenation
Utilising digital twins to optimise mechanical ventilation settings for a patient receiving ECMO.