Centre for Doctoral Training in AI-enabled Healthcare


Machine learning for patient stratification and outcome prediction from ‘real world evidence’

24 January 2020, 12:30 pm–1:30 pm


Join us on the 24th January to hear Ben Irving (Sensyne Health) speak about machine learning for patient stratification and outcome prediction from ‘real world evidence’. This seminar will be the fourth in our Future of AI in Healthcare CDT Seminar Series.

Event Information

Open to





Craig Smith – UCL Institute of Health Informatics


Institute of Health Informatics
222 Euston Road

Electronic health records (EHR) and other medical data (such as medical images) has potential to find substructures or subtypes of disease.

For example, within heart failure there are currently recognised differences in a patient’s heart efficiency. A measurement system to assess this efficiency difference – known as “ejection fraction”, measures the percentage of blood leaving and entering the heart. Approximately half of people with heart failure have preserved ejection fraction, while the other half have reduced ejection fraction. Rather than only using clinically driven parameters, machine learning offers an opportunity to take data driven approaches based on the patient diagnosis pathway to better predict outcomes or stratify disease subtypes.

In this talk, Ben will discuss Sensyne Health’s approach in using AI to personalise treatment and provide examples of the type of analysis being performed at Sensyne Health.

About the Speaker

Ben Irving

Machine Learning Team Lead at Sensyne Health

Ben is a Machine Learning Team Lead at Sensyne Health. He has an MSc in Biomedical Engineering, and a PhD in Computer Assisted Detection and Medical Imaging from University College London. After completing his PhD, Ben worked as a researcher at the University of Oxford on machine learning approaches for characterisation of tumours and response to therapy. Before joining Sensyne Health in 2019, he was an Imaging Scientist at Perspectum Diagnostics in Oxford UK.


More about Ben Irving