Andrew P. Creagh

Institute of Biomedical Engineering (IBME),
Old Road Campus Research Building (ORCRB),
University of Oxford,
OX37DQ, UK.
Welcome
I am a Digital Health & AI/ML Researcher based at the Computational Health Informatics (CHI) laboratory at the University of Oxford led by Prof. David A. Clifton.
I am concurrently a GSK Postdoctoral Fellow in Digital Biomarkers, a Junior Research Fellow at St Cross College, University of Oxford, and a Postdoctoral Researcher at the Oxford Wearables Laboratory led by Prof. Aiden Doherty at the Big Data Institute (BDI), University of Oxford.
My Research Profiles:
Dept. of Engineering Science Website
Big Data Institute Website
St Cross College Website
Research
My research aims to explore how we can capture digital biomarkers of disease using consumer digital health technologies (DHT)—collected from smartphone and smartwatch app. sensors and patient reported outcomes (PROs) when patients are at home—to develop personalised monitoring, enhance patient treatment strategies, uncover digital phenotypes, and ultimately the development of validated digital biomarkers for clinical trial (CT) end-points and prescribed digital therapeutics (DTx). I have worked with CT data from patients in a range of Therapeutic Areas (TA) from multiple sclerosis to Parkinson’s disease, rheumatoid arthritis and dementia.
Clinical applications of AI/ML (machine learning) can act as powerful tools to learn complex and unseen digital patterns of disease, to help remotely monitor and identify signs of degeneration before they occur, and to understand new facets of habitual disease and disease phenotypes. My technical areas of expertise include AI/ML for disease prediction, explainable AI (XAI), and time-series analysis. I have a specific interest in creating interpretable, robust, and validated digital biomarkers through explainable AI (XAI) frameworks.
Background
I obtained my DPhil. (PhD) in Clinical Machine Learning at the University of Oxford, developing digital biomarkers in collaboration with industrial partners, F. Hoffmann-La Roche.
Prior to my DPhil. I hold a bachelor’s degree (BAI, BA) in Biomedical Engineering and master’s degree (MAI) in Neural Engineering from Trinity College, the University of Dublin. My research at Trinity investigated the use of machine learning techniques to predict the onset of dementia in later life, through the characterisation of gait and cognitive performance from routine clinical assessments conducted during the Irish Longitudinal Study on Aging (TILDA).
News
May 20, 2023 | Excited to be speaking at the upcoming Pint of Science Festival in Oxford. I’m going to try debunk the 10,000 steps a day myth! ⌚ |
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Mar 1, 2023 | Check out my latest blog post, where I summarise our recent work on ‘Synthesizing Mixed-type Electronic Health Records using Diffusion Models’, which is now available on arXiv! 📢 |
Jan 12, 2023 | Excited to be speaking at the upcoming IoT Clinical Trials Europe conference in London, where I will discuss the opportunities for digital health technologies (📱/⌚) and AI/ML to augment decentralised clinical trials 👥📢 |
Jan 5, 2023 | In in my latest blog post, I discuss what we learned in our new journal paper, which was recently published in IEEE OJEMB 💡 |
Nov 23, 2022 | Check out our latest blog post, where we discuss the key findings, learnings, and impact of the WeaRAble-PRO study in RA 💡 |
Nov 19, 2022 | Our new preprint: “Digital health technologies and machine learning augment patient reported outcomes to remotely characterise rheumatoid arthritis” is now available on medrXiv 📢. |
Aug 23, 2022 | We have now publicly released our code for our paper: “Mixture of Input-Output Hidden Markov Models for Heterogeneous Disease Progression Modeling” from ICML on GitHub . |
Jun 18, 2022 | Our new preprint: “Self-supervised Learning for Human Activity Recognition Using 700,000 Person-days of Wearable Data” is now available on arXiv 📢. |
Feb 24, 2022 | Our new preprint: “Longitudinal Trend Monitoring of Multiple Sclerosis Ambulation using Smartphones” is now available on medrXiv 📢. |
Nov 1, 2021 | Announced as this year's recipient of the prestigious IET William James Award 🥳. |
Jul 15, 2021 | Our new explainable AI (XAI) paper is now available online in Nature Scientific Reports 🥳. |
Jun 16, 2021 | Awarded Junior Research Fellowship (JRF) St Cross College, University of Oxford. |
Apr 12, 2021 | Awarded STEM for Britain Medal at the UK Houses of Parliament |
Dec 21, 2020 | Our Draw a Shape paper was the most cited paper in Physiological Measurements in 2020! |