Spiros is joining the BHF Data Science Centre, led by Health Data Research UK (HDR UK), on a part-time secondment basis to provide strategic leadership focused on the development, refinement and use of reproducible and innovative phenotyping algorithms for cardiovascular research. This thematic area will use a wide range of health datasets (e.g. hospital admissions, primary care, medicines data, cohorts, biomarkers, imaging, free text) to describe cardiovascular symptoms, risk factors and diseases in computable form. This work is essential for the delivery of research into the causes, prediction, progression and management of heart and circulatory diseases, demonstrating impact at national and international level.
Spiros is Professor of Biomedical Informatics at the Institute of Health Informatics, University College London. His research focuses on the creation and evaluation of algorithms for identifying and validating disease phenotypes in large-scale structured electronic health records, clinical and genomics data. This includes the creation of the Health Data Research UK Phenotype Library, a national open access library which enables research reproducibility by curating algorithms, codelists, metadata and associated documentation of over 750 phenotypes for the wider scientific community.
“I’m super excited to be joining the BHF Data Science Centre team to lead this key thematic area. Creating reproducible and validated phenotyping algorithms will enable researchers and clinicians to fully utilize the rich information that electronic health records contain and to undertake clinically meaningful research that will ultimately improve human health and healthcare.”
Prof Cathie Sudlow, Director of the BHF Data Science Centre said:
“The BHF Data Science Centre team is delighted to welcome Spiros to work with us to shape our priorities in the development and use of computable cardiovascular phenotypes. Spiros’ leadership will help us to make real progress towards ensuring that robust and reproducible computable phenotypes from large-scale health data can be developed and validated for a wide range of cardiovascular research studies.”
Computable cardiovascular phenotypes is one of six key thematic areas at the BHF Data Science Centre. This thematic area will focus on identifying priority research questions and driving the development of computable phenotypes across a wide range of health data, identifying and linking new data sources where appropriate. This work will help the centre to achieve its overall vision – to improve the public’s cardiovascular health through the power of large-scale data and analytics across the UK.
Thematic Area: Computable Phenotypes
What do we mean by ‘computable phenotypes’? This means looking at ways of clearly defining different types of cardiovascular diseases (such as types of strokes, heart attacks and clots) in a...