MBBS BSc MRes DMCC MRCA
Senior Research Fellow in Health Data Science
Chris Tomlinson is an Anaesthetics & Intensive Care registrar undertaking a PhD at the UKRI UCL Centre for Doctoral Training in AI-enabled Healthcare Systems.
Combining technical expertise in epidemiology, data science and machine/deep learning with an extensive background in clinical medicine and physiological research he uses real world evidence to uncover new insights of critical relevance to patients, clinicians and policymakers. Most recently this has involved creating novel COVID-19 phenotypes from linked-EHR data of 57 million individuals in England (now published in Lancet Digital Health).
He is interested in the application of AI methodologies to disentangle the complex interactions between organ systems, diseases, individuals and healthcare services to advance our scientific understanding and translate knowledge into tangible benefits to patient care.
Chris enjoys productive collaborations spanning computer science, health informatics and clinical medicine across UCL institutions, other universities within the UK, and abroad, as well as organisations such as Health Data Research UK, British Heart Foundation Data Science Centre, The Alan Turing Institute and Wellcome Trust and industry partners such as GSK, Databricks and AWS.
He strongly believes in the value of multidisciplinary collaboration for delivering responsible innovation and impacts, particularly in complex areas such as healthcare and biomedicine, as well as relishing the learning opportunities that this provides.
This ethos is reflected in a wide range of co-authors, as visualised in the interactive network diagram below:
For July’s BHF Data Science Centre webinar we were joined by Professor Kate Brown from Great Ormond Street Hospital (GOSH) and Dr Chris Tomlinson from University College London (UCL). They speak about findings from a recent paper, published on 5th July 2023, outlining the impact of COVID-19 on children across England. This study - undertaken as part of the BHF Data Science Centre CVD-COVID-UK/COVID-IMPACT Consortium – looked at 12 million childhood health records across England during the height of the pandemic, and analysed 3.2 million cases of coronavirus infection. The study reveals the extent of severe outcomes in children during the pandemic and could inform public health policies.
A joint webinar hosted by National Institute for Health Research (NIHR) and British Heart Foundation (BHF) Data Science Centre for NIHR supported COVID-19 studies, to highlight how to utilise and access routinely-collected healthcare data via NHS Digital’s Trusted Research Environment, the UK’s largest linked health data research asset.