Turing Health and Medical Sciences Programme
The Turing Health and Medical Sciences Programme at Leeds
The aim of the Turing’s health and medical sciences programme is to accelerate the scientific understanding of human disease and improving human health through data-driven innovation in AI and statistical science. Learn more
- Rapid Assistance in Modelling the Pandemic (RAMP)
Turing Programme Director for Urban Analytics and Director of LIDA, Professor Mark Birkin has been tasked with leading a key work stream of The Rapid Assistance in Modelling the Pandemic (RAMP) initiative which is bringing modelling expertise from a diverse range of disciplines to support the pandemic modelling community working on Coronavirus. Coordinated by the Royal Society, RAMP is helping to model the Coronavirus (COVID-19) pandemic and guide the UK’s response. Professor Birkin’s expertise will help to connect epidemic models to transport and urban analytics. Learn more.
- DECOVID project
The Alan Turing Institute DECOVID project will provide up to date information about patient care during the COVID-19 pandemic. This information will be analysed to answer the most pressing clinical questions to support the COVID-19 emergency response and to improve the quality of patient care for the future.
A team of LIDA academics and researchers will contribute to the DECOVID Analytics work stream. Led by Turing Fellows Dave Westhead and Roy Ruddle, the LIDA team will provide important expertise to the DECOVID programme in the analysis of national data sets and machine learning in health care applications, and in data mining and visualization. Further expertise will be provided in areas such as epidemiology, electronic health records, ICU data and coding and causal inference methodology. Data analysis work will be carried out by a team of LIDA post-doctoral fellows, PhD students and project interns. Learn more about the DECOVID project.
British Heart Foundation-Alan Turing Institute Cardiovascular Data Science Award
Dr Marlous Hall and Dr Jianhua Wu have successfully been awarded a British Heart Foundation-Alan Turing Institute Cardiovascular Data Science Award. The award, which aims to promote multi-disciplinary research to generate data science solutions to key cardiovascular problems, will be used to investigate suitable methods to understand disease pathways following a heart attack at scale.
Whilst a heart attack can be fatal, a large number of people do survive upon receipt of urgent medical care. Despite this, a heart attack can leave people at increased risk of developing further health conditions later in life. The full extent of which conditions are likely to develop following a heart attack, and in what timeframe, are unknown. Therefore, this project aims to study 145 million anonymised hospital records for patients across the whole of England to provide rich information on the temporal pathways of diseases which may follow a heart attack. However, the most appropriate methods needed to study such large volumes of data containing thousands of unique disease codes in a sequence at unstructured time intervals are not yet known. This pilot study will aim to investigate the most appropriate statistical and machine learning methods to do so. This will not only inform the wider research community, but also has the potential to provide detailed clinical evidence of the long term health consequences of a heart attack.