Chris Tomlinson

👨‍💻Health Data Scientist |🎓PhD in AI Healthcare |👨‍⚕️Critical Care Doctor

Biography

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.

Interests

Phenomics: Defining clinically-relevant EHR phenotypes to unlock routinely-collected healthcare data for research benefit
Representation learning: building predictive representations that codify both domain knowledge and data-driven insights
Uncertainty quantification: for clinical evaluation and scientific discovery
Causal inference: for evidence generation from routinely-collected observational data

Education

PhD Candidate: Artificial Intelligence enabled healthcare, 2021-2024
UKRI UCL Centre for Doctoral Training in AI-enabled Healthcare Systems, UCL Institute of Health Informatics
MRes Artificial Intelligence enabled healthcare, 2021
UKRI UCL Centre for Doctoral Training in AI-enabled Healthcare Systems, UCL Institute of Health Informatics
MRCA (Primary Fellowship), 2018
Royal College of Anaesthetists
Diploma in Medical Care of Catastrophes, 2016
The Worshipful Society of Apothecaries of London
Bachelor of Medicine & Surgery, 2014
University College London
Bachelor of Medical Sciences with Physiology (1st Class Hons), 2011
University College London

Feed

Should you be interested, you can follow my latest updates on Twitter @tomlincr:

Collaborators

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.

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:

Projects

Automated Assessment of Vascular Perfusion (Alan Turing Institute Data Study Group)

🎯 Automated assessment of vascular perfusion 🎓 Challenge owner: Prof Tony Whitehouse (University Hospital Birmingham, University of Birmingham) 🎓 Principle Investigator: Dr Kashif Rajpoot (University of Birmingham) 🏆 Received the ‘super additive’ award for ‘championing collaboration & knowledge exchange’

CVD-COVID-UK/COVID-IMPACT Consortium

Contributing clinical experience, data wrangling and analytical skills to development of COVID-19 Severity phenotypes from linked EHR data for 54 million patients in England.

Xtreme Everest 2

Large expedition to Everest Base Camp seeking to characterise acclimatisation to environmental hypoxia in Sherpa’s & Westerners to identify biomarkers of (mal-) adaptation that may inspire novel diagnostic/therapeutic targets for the cellular hypoxia seen in critical illness.

Innovation in Transtracheal Airway Design

Inaugural ‘Innovation in Anaesthesia’ BSc project leading to multidisciplinary and industrial collaboration

Featured Publications

Quickly discover relevant content by filtering publications.

Christina Pagel, Harrison Wilde, Chris Tomlinson, Bilal Mateen, Katherine Brown (2023). A Methodological Framework for Assessing the Benefit of SARS-CoV-2 Vaccination following Previous Infection: Case Study of Five- to Eleven-Year-Olds. Vaccines.

DOI

Caroline E Dale, Rohan Takhar, Raymond Carragher, Michalis Katsoulis, Fatemeh Torabi, Stephen Duffield, Seamus Kent, Tanja Mueller, Amanj Kurdi, Stuart McTaggart, Hoda Abbasizanjani, Sam Hollings, Andrew Scourfield, Ronan Lyons, Rowena Griffiths, Jane Lyons, Gareth Davies, Daniel Harris, Alex Handy, Mehrdad Alizadeh Mizani, Chris Tomlinson, Johan Thygesen, Mark Ashworth, Spiros Denaxas, Amitava Banerjee, Jonathan Sterne, Paul Brown, Ian Bullard, Rouven Priedon, Mamas A Mamas, Ann Slee, Paula Lorgelly, Munir Pirmohamed, Kamlesh Khunti, Andrew Morris, Cathie Sudlow, Ashley Akbari, Marion Bennie, Naveed Sattar, Reecha Sofat, CVD-COVID-UK Consortium (2023). The impact of the COVID-19 pandemic on cardiovascular disease prevention and management. Nat Med.

PDF Code Dataset DOI

Rochelle Knight, Venexia Walker, Samantha Ip, Jennifer A Cooper, Thomas Bolton, Spencer Keene, Rachel Denholm, Ashley Akbari, Hoda Abbasizanjani, Fatemeh Torabi, Efosa Omigie, Sam Hollings, Teri-Louise North, Renin Toms, Xiyun Jiang, Emanuele Di Angelantonio, Spiros Denaxas, Johan H Thygesen, Chris Tomlinson, Ben Bray, Craig J Smith, Mark Barber, Kamlesh Khunti, George Davey Smith, Nishi Chaturvedi, Cathie Sudlow, William N Whiteley, Angela M Wood, Jonathan A C Sterne, CVD-COVID-UK/COVID-IMPACT consortium, Longitudinal Health and Wellbeing COVID-19 National Core Study (2022). Association of COVID-19 With Major Arterial and Venous Thrombotic Diseases: A Population-Wide Cohort Study of 48 Million Adults in England and Wales. Circulation.

PDF Code Dataset Video DOI

Chris Tomlinson, Jan Grols, Ramit Debnath, Sarah Johnson, Max Barton, Tianyu Han, Seyedeh Nazanin Khatami, Giacomo Baldo, Aniketh Ramesh, Diego Cammarano, Kashif Rajpoot (2022). Automating perfusion assessment of sublingual microcirculation in critical illness.

DOI

Johan H Thygesen, Chris Tomlinson, Sam Hollings, Mehrdad Mizani, Alex Handy, Ashley Akbari, Amitava Banerjee, Jennifer Cooper, Alvina Lai, Ken Li, Bilal Mateen, Naveed Sattar, Reecha Sofat, Ana Torralbo, Honghan Wu, Angela Wood, Jonathan A C Sterne, Christina Pagel, William Whiteley, Cathie Sudlow, Harry Hemingway, Spiros Denaxas, on behalf of the CVD-COVID-UK Consortium (2022). COVID-19 trajectories among 57 million adults in England: a cohort study using electronic health records. Lancet Digital Health.

PDF Code Dataset DOI

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Featured Presentations

Dr Chris Tomlinson

Mar 16, 2022 12:00 AM Online

BHF Data Science Centre Research Showcase: Phenotyping COVID-19: Insights from linked data for 56 million individuals

Prof Nick Lemoine, Prof Martin Gibson, Prof Cathie Sudlow, Dr Angela Wood, Dr Venexia Walker, Dr Johan Thygesen, Dr Chris Tomlinson, Lynn Morrice

Sep 14, 2021 12:00 AM Online

NIHR & BHF Data Science Centre Webinar: Data Linkage for COVID-19 Research

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.

J Thygesen, C Tomlinson, S Denaxas & CVD-COVID-UK Consortium

Jun 16, 2021 12:00 AM Online

Characterising COVID-19 related events in a nationwide electronic health records cohort in England

Short presentation of our progress on defining COVID-19 event phenotypes in the NHS-Digital Trusted Research Environment as part of the CVD-COVID-UK Consortium.

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