Directory of Expertise
The following research areas are our main areas of expertise. Learn more about the research and the experts involved.
Addressing the barriers to translating machine learning algorithms into patient benefit, with a particular focus on data-scarce learning and dataset drift on structured time-series EHR datasets.
Contact:
Dr Xi Bai
Prof Amitava Banerjee
Mr Alex Handy
Dr Abul Hasan
Mr Thomas Keen
Dr Ken (Kezhi) Li
Dr Watjana (Waty) Lilaonitkul
Dr Farhad Shokraneh
Dr Johan Thygesen
Dr Honghan Wu
Cardiovascular diseases (CVD) and their risk factors, some of which are diseases in their own right, such as hypertension and diabetes, represent the largest burden of morbidity and mortality not just in the UK, but worldwide. Our researchers at IHI use “big data” approaches in translational research across aetiology, diagnosis, treatment and prevention of CVD.
Contact:
Prof Folkert Asselbergs
Dr Ruth Blackburn
Mr Alex Handy
Mr Albert Henry
Dr Maria Krutikov
Dr Tom Lumbers
Dr Johan Thygesen
Dr Ana Torralbo
Integrating electronic health records with diverse data sources (omics, qualitative research) to improve the management of infection across health and social care settings.
Contact:
Dr Maria Krutikov
Prof Laura Shallcross
Utilising routine and administrative data to understand the health of children and families, and evaluate policy impact.
Contact:
Dr Ruth Blackburn
Dr Zhiqiang Huo
Dr Alvina Lai
Developing knowledge-driven models by deploying AI algorithms and natural language processing techniques to achieve dermatology triage based on GPs' referrals. The volume of healthcare data continues to grow, as does the work required to analyse it. However, this has yet to produce a significant number of actionable insights that could improve patient outcomes. We do not yet have a strong evidence base for many treatments and interventions given in routine clinical care. Clinical actions are currently driven by expertise instead of evidence from randomised controlled trials (RCTs) that are expensive, and labour and time intensive to conduct. Variations in care may therefore reflect both a lack of evidence or suboptimal guideline adherence. However, by harnessing digital tools and data-enabled trials, it is possible that we can reduce the gap between evidence and practice in healthcare. The increasing use of clinical decision support systems (CDSS) gives us the opportunity to use computer prompts called digital ‘nudges’ to modify clinician behaviour and improve adherence to guideline-directed therapy. What is more, ‘nudging’ gives us the opportunity to initiate data-enabled randomised controlled trials in areas where strong evidence is particularly lacking.
Contact:
Prof Folkert Asselbergs
Dr Zhiqiang Huo
Dr Ken (Kezhi) Li
Dr Watjana (Waty) Lilaonitkul
Dr Tom Lumbers
Dr Anoop Shah
Integrating data from routine and administrative sources, as well as from observational studies and clinical trials to describe the epidemiology and outcomes of Covid-19 infection in different populations.
Contact:
Prof Folkert Asselbergs
Prof Amitava Banerjee
Dr Maria Krutikov
Prof Laura Shallcross
Ms Sophie Weber
Data linkage aims to bring together information from two or more different sources to create a new, richer dataset. Data may be linked for different units including individuals, organisations, geographical areas, or time points.
Working on an ontology enrichment project to predict drug targets based on existing knowledge graphs.
Contact:
Mr Albert Henry
Dr Watjana (Waty) Lilaonitkul
An electronic health record (EHR) is the systematised collection of patient health information in a digital format. EHR are commonly derived from general practices and hospitals and may include information on demographics and biometrics such as height and weight, medical history, medication and allergies, immunisations, laboratory test results, medical imaging, vital signs, and billing information. We analyse longitudinal patient data from primary and secondary care electronic health records, extract concepts and structure information from free text, and develop methods that utilise the limitations and strengths of this valuable data resource. The overall aim is to improve patient care using patient information.
Contact:
Prof Folkert Asselbergs
Prof Amitava Banerjee
Dr Ruth Blackburn
Mr Alex Handy
Mr Albert Henry
Dr Maria Krutikov
Dr Alvina Lai
Dr Watjana (Waty) Lilaonitkul
Dr Tom Lumbers
Dr Anoop Shah
Prof Laura Shallcross
Dr Johan Thygesen
Dr Ana Torralbo
Ms Cai Ytsma
Aiming to enhance our understanding of how environmental exposures, including climate change, impact human health, particularly those who are the most vulnerable in our population and at critical periods (for example, in utero).
Epidemiology is the systematic study of the distribution, trends and causes of disease within populations, and can also encompass the study of disease prevention and control that applies epidemiological methods.
Contact:
Prof Rob Aldridge
Dr Xi Bai
Prof Amitava Banerjee
Dr Ruth Blackburn
Dr Yamina Boukari
Dr Isobel Braithwaite
Mr Alex Handy
Mr Albert Henry
Dr Maria Krutikov
Dr Alvina Lai
Prof Laura Shallcross
Dr Farhad Shokraneh
Ms Sophie Weber
Evidence synthesis is finding, screening, critically appraising, synthesising, analysing, and summarising the existing evidence to answer the research, policy, or practice question.
Genomics research focuses on the identification and characterisation of genetic variants that contribute to the risk of developing disease or effect patient outcome or treatment.
Contact:
Prof Folkert Asselbergs
Mr Albert Henry
Dr Tom Lumbers
Dr Johan Thygesen
We study ways to structure the information in health records to ensure that its meaning is preserved, and information can easily flow between systems for better patient care and research. Software interoperability is the ability of different computer systems to effectively exchange or share data with immediate use and understanding of the exchanged information. Standards for clinical data models refer to the development of a standardised data structure and description to enhance the interoperability of clinical data databases.
Contact:
Dr Watjana (Waty) Lilaonitkul
Dr Vaclav Papez
Dr Anoop Shah
Studying the health of migrants, including their healthcare utilisation and outcomes. Health inequalities are avoidable differences in health between groups based on certain characteristics, such as age, sex and gender, disability, deprivation or ethnicity. This research identifies those inequalities and proposes strategies to address them.
Contact:
Prof Amitava Banerjee
Dr Yamina Boukari
Dr Ana Catarina (Cat) Pinho Gomes
Dr Mel Ramasawmy
Dr Honghan Wu
Health research using observational data involves the description and analysis of data from observational epidemiological studies or routine data collection (as opposed to experimentally-collected data), to improve understanding of the epidemiology of disease and the impacts of exposures and interventions.
Contact:
Dr Isobel Braithwaite
Aiming to equitably improve the health of the public through the application of data science and public health research.
Contact:
Prof Amitava Banerjee
Dr Ruth Blackburn
Prof Rob Aldridge
Dr Alvina Lai
Professor Laura Shallcross
Phenomics is concerned with the measurement of observable characteristics of an individual over time and in response to genetic and environmental influences.
Contact:
Dr Xi Bai
Prof Amitava Banerjee
Dr Ruth Blackburn
Mr Alex Handy
Dr Alvina Lai
Dr Ken (Kezhi) Li
Dr Watjana (Waty) Lilaonitkul
Dr Tom Lumbers
Dr Anoop Shah
Prof Laura Shallcross
Dr Johan Thygesen
Dr Honghan Wu
Precision medicine aims to deliver clinically relevant disease phenotypes and outcomes, scalable insights from real-world evidence from electronic health records and registries and -omics research for drug target discovery, pharmacogenetics and stratified medicine and insights driving drug development and personalised medicine through advanced big-data analytics.
Contact:
Prof Folkert Asselbergs
Prof Amitava Banerjee
Mr Alex Handy
Dr Alvina Lai
Dr Ken (Kezhi) Li
Dr Watjana (Waty) Lilaonitkul
Dr Tom Lumbers
Prof Laura Shallcross
Dr Honghan Wu
Public health has been defined as 'the science and art of preventing disease, prolonging life and promoting health through the organised efforts and informed choices of society, organisations, public and private, communities and individuals'.
Reducing unjust and avoidable inequalities in health is also a core element of public health. It encompasses and draws on a broad range of related disciplines including epidemiology and statistics, evaluation and applied health research, sociology, health economics and policy.
Contact:
Prof Rob Aldridge
Prof Amitava Banerjee
Dr Ruth Blackburn
Dr Yamina Boukari
Dr Isobel Braithwaite
Dr Maria Krutikov
Dr Alvina Lai
Prof Laura Shallcross
Dr Farhad Shokraneh
Dr Ana Torralbo
Dr Honghan Wu
Developing methodology to integrate relevant patient information to understand and model risk for diseases on an individual or population basis.
Contact:
Prof Amitava Banerjee
Mr Alex Handy
Mr Albert Henry
Dr Alvina Lai
Dr Ken (Kezhi) Li
Dr Watjana (Waty) Lilaonitkul
Prof Laura Shallcross
Dr Johan Thygesen
Sex and gender research focuses on differences in health between males vs females and women vs men in health, and the epidemiology and management of diseases. In women's health, we aim to improve the health of women across the life course.
Software development refers to computer science activities like software design, coding and programming, testing, and documenting performed in order to create a computer program or application.
Contact:
Dr Xi Bai
Mr Alex Handy
Dr Ken (Kezhi) Li
Dr Watjana (Waty) Lilaonitkul
Dr Vaclav Papez