The in-house iCARE research and analytics team brings together expertise in data science, data engineering, clinical research and healthcare innovation.

Our team specialises in translational research, with every project supported by a clinical sponsor to ensure our work is grounded in NHS priorities and frontline expertise. From saving lives to supporting digital transformation, our work is improving care across North West London while generating insights and innovations with potential to benefit the wider NHS.

Explore our impact stories below to see our work in action.

 

Deploying AI in a live NHS system

AI-Enabled identification of hospitalised smokers

iCARE has successfully translated AI research into practice by deploying machine learning within a live NHS system. The tool identifies hospitalised smokers from free-text clinical records, enabling Health Improvement Teams to receive daily, actionable lists and deliver timely interventions to patients who might otherwise be missed.

Featuring

Maite Arribas Ardura | Pradeepa Maheshkumar

Bringing Generative AI into clinical workflows

AI-Assisted discharge summary generation

iCARE is bringing Generative AI into the clinical workflow, developing and evaluating an AI pipeline that generates discharge summaries from clinical notes. The work explores how AI can support high-quality documentation and safer transitions between hospital and community care.

Featuring

Kathleen Goldsmith | Sailesh Varsani | Pradeepa Maheshkumar | Yamuna Indiran

Turning NHS data into proactive patient safety

AI-Enabled falls prevention

iCARE is helping transform how patient safety insights are generated by integrating fragmented NHS incident data into a near real-time analytics platform. By bringing information together in one place, the system helps teams identify trends, understand risks, and support earlier action to prevent falls.

Featuring

Yusuf Abdullahi | Kenneth Mok | Mirel Fernandes

Automating VTE risk assessment

AI-Enabled venous thromboembolism risk assessment

Venous thromboembolism (VTE) is a leading cause of preventable inpatient mortality. iCARE researchers are exploring how machine learning and electronic health record data can support automated VTE risk assessment, enabling earlier identification of patients at risk and more timely clinical decision-making.

Virtual ward round

Real-Time Diabetes Risk Detection at Scale

iCARE is exploring how routine hospital data can be used to identify clinical risk as it happens. Our work shows that EHR data can support real-time detection of diabetes and treatment-related risks across large inpatient populations, creating opportunities for earlier intervention and safer care.

Contact us

For general enquiries email: imperial.dcs@nhs.net

For data access enquiries email: imperial.dataaccessrequest@nhs.net

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