Chris is a senior research fellow in health data science and clinical PhD student at UCL, on track to submit his thesis on informatics and AI-based approaches for scalable phenotyping of electronic health records (EHR), in early 2024.
He has over a decade of experience in healthcare, spanning physiological research and clinical medicine, as well as quantitative methods in epidemiology and machine learning. His work has been featured in top medical journals (Nature Medicine, Circulation, BMJ, Lancet Digital Health) and informed policy at home and abroad.
He is excited about the ability of artificial intelligence to flexibly integrate, structure and summarise insights from both traditional knowledge repositories and observational data, to scalably advance our understanding of health and disease, and enable us to address the fundamental challenges of precision medicine: diagnosis, prognosis and treatment response.
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.