Up to 30% of patients admitted to hospital with COVID (novel coronavirus infection) will require admission to an intensive care unit (ICU) and potentially help with breathing via a ventilator.
We will develop statistical and artificial intelligence approaches to predict which patients are most likely to require admission to ICU and ventilation. These tools will be based on a snapshot of the information available when a patient is admitted to hospital, as well as new information that become available during a patient’s hospital stay.
Our approaches aim to allow patients needing ICU care to be identified earlier to allow their care to be prioritised.
Development and validation of early warning score systems for COVID-19 patients
Rapid triage for COVID-19 using routine clinical data for patients attending hospital
Real-world evaluation of rapid and laboratory-free COVID-19 triage for emergency care: external validation and pilot deployment of artificial intelligence driven screening
Machine learning generalizability across healthcare settings: insights from multi-site COVID-19 screening