Staff Services Student Enterprise

Digital Health Innovation Engine

Bespoke solutions based on University of Edinburgh expertise

Key capability

  • Unique ‘cradle to grave’ electronic record linkage for a stable population of 5m
  • Dedicated health and social care data repository – DataLoch (data from 1m+ patience including large-scale longitudinal studies)
  • Bespoke datasets covering COVID-19, retinal scans, speech data, genomics and more
  • Edinburgh Medical School, on-campus teaching and research hospitals
  • World-class cardiology, respiratory, neurology (No1 in UK, REF 2021), diabetes and more
  • On-campus Clinical Research Facility, MHRA Phase 1 accredited allowing first-in-human and Phase 1 trials
  • Largest bioinformatics hub in Europe
  • No1 in UK for computer science and informatics (REF 2021)
  • AI established at the University of Edinburgh for 60 years, >500 AI researchers
  • £660m Data-Driven Innovation Programme recognising Edinburgh as the Data Capital of Europe

Healthy ageing and agetech capability

  • Uses sophisticated medical imaging methods eg MRI to determine how SVD affects the brain and blood vessels
  • Developed highly specialised computer methods to analyse MRI images. Analysis tools and image databanks from our studies enable the earlier detection and diagnosis of SVDs and new methods for prevention and treatment.
  • Novel image processing algorithms for use in cutting-edge medical imaging as well as retinal imaging-derived biomarker identification for neurodegeneration and systemic disease.
  • Coordinator of the international initiative, VAMPIRE (Vessel Assessment and Measurement Platform for Images of the retina), a software application for efficient, semi-automatic analysis of retinal images.
  • Use of eye-tracking to study a wide range of human behaviour, including language processing, reading, visual cognition, dialogue and interaction.
  • Working in the field and simulated environments with portable eye trackers and head-mounted displays, the data generated underpins the construction of computational models that simulate and predict human cognitive processes, often in real time.
  • Outcomes can be used to understand the behaviour of older adults in care home environments to predict and recognise situations that require intervention.
  • Longitudinal monitoring of neurodegenerative disorders by integrating wearable sensors and smartphones to elicit daily responses from people with Parkinson's disease and motor neurone disease.
  • Mental health assessment using wearable sensors and smartphones.
  • Novel data-driven strategies for cardiovascular disease assessment as well as biomedical speech signal processing.

Academic Champions

Professor Sir Aziz Sheikh OBE

Director of the Usher Institute

Directorship of the Usher Institute, the Asthma UK Centre for Applied Research (AUKCAR), the NIHR Global Respiratory Health Unit (RESPIRE) and Co-Director of the NHS Digital Academy. Primary care academic and epidemiologist with a history of over $90m in research grants and over. 50,000 citations of published research.

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Professor Siddarthan Chandran

Dean of Clinical Medicine

Professor of Neurology, Director of the Centre for Clinical Brain Sciences, Head of Department of Clinical Neuroscience, Director of Edinburgh Neuroscience and Programme Lead of the UK Dementia Research Institute at the University of Edinburgh.

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Professor Andrew Morris

Inaugural Director of Health Data Research UK, Co-founder of Aridhia Informatics, using high-performance computing and analytics in healthcare, Pioneering Digital Therapeutics development based on innovation from the UK’s data repositories, Former CEO of PhenoTherapeutics.

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Professor Joanna Wardlaw

Director of the Row Fogo Centre for Research into Ageing and the Brain and internationally recognised for her research on the pathophysiology of cerebral small vessel diseases (SVDs) and brain ageing. SVDs have been recognised to be a main cause of age-related brain diseases such as stroke, dementia and Alzheimer’s disease, but our understanding of SVDs is still limited.

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Dr Tom McGillivray

Specialising in image processing and analysis, Dr MacGillivray’s key interest is retinal imaging and how the retina can provide insights into the health of the brain using computational analysis of retinal images important for example in stroke and dementia.

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Professor Frank Keller

Professor Keller’s research focuses on language and vision, cognitive modelling, eye-tracking, and applications of deep learning. His expertise in computational models can predict and simulate human behaviour in real time.

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Dr Thanasis Tsanas

Dr Tsanas develops and applies novel time series, signal processing, pattern recognition, and statistical machine learning algorithms to provide insight into data and address unmet needs (primarily healthcare). Applications include longitudinal telemonitoring of chronic diseases, natural language processing, data fusion, multi-sensor processing, and biomechanics.

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