biomedical sciences medical technology man


Professor Brendan Delaney

What we do

We work in the area of health systems for research and knowledge translation, known as the Learning Health System. Creating cycles of data, captured at the point of care, informing advanced analytical methods to derive knowledge for diagnosis or treatment. Knowledge is then expressed in a computable format, operating via Decision Support Systems (DSS) integrated with routine Electronic Health Record systems to support clinical care of individual patients. We work closely with colleagues in the Dept of Computing and in other institutions as well as industry and the NHS.

Why it is important

Health systems in both advanced and developing countries face challenges in delivering safe and effective care that is cost-effective yet tailored to individual patient needs. Diagnostic error and delay cause significant harm to patients worldwide and in primary care represent the largest cause of patient harm. AI built into EHR systems offers the potential for real time differential diagnosis generators and alerts for complex clinical care pathways, but the underlying data and knowledge need to be represented in reliable computable forms, this is where medical informatics has its role.

How it can benefit patients

Diagnosis and selecting the correct treatment amongst conflicting alternatives can be aided by well-designed information systems that integrate with EHR systems and bring the benefits of Artificial Intelligence into the clinical encounter. In addition, better management of data allows richer information to be used in research and monitoring of clinical care.

Summary of current research

Developing a Learning Health System for diagnosis in primary care, capable of supporting an individual patient based-differential diagnosis generator integrated with the primary care EHR. CRUK funded.

ROAD2H: Artificial Intelligence for clinical practice guidelines that produces reasoned arguments in favour of particular treatments for individual patients. Joint project with the Dept of Computing. EPSRC Global Health project

RECAP: Developing and validating a risk score to predict hospital admission for patients with acute COVD-19 in Primary Care. Joint project with the University of Oxford. Funders UKRI and Imperial Jameel Community Fund.

Additional information

Our researchers

Mr Denys Prociuk

Mr Denys Prociuk

Mr Denys Prociuk
Technical Analyst