Dr Iain Marshall
Clinical Senior Lecturer in Population Health Sciences
Biography
Dr Iain Marshall is a population health scientist, and south London GP. His diverse research interests include artificial intelligence/natural language processing systems to support health decision-making, systematic review methodology, and stroke and cardiovascular disease prevention. Iain co-leads the RobotReviewer project, which aims to use machine learning to automate (or semi-automate) systematic reviews.
Iain is the Royal College of General Practitioners (RCGP) national Clinical Champion for Stroke. He is the GP member of the Intercollegiate Stroke Working Party, and is on the guideline development group for the 2023 National Clinical Guideline for Stroke. He is the Chief Investigator of the South London Stroke Register, and of the NIHR Programme Grant: Improving the lives of stroke survivors with data.
Iain is a Clinical Senior Lecturer at King's, and is an NHS GP and partner at the Greyswood Practice, Streatham. He supervises PhD students in health data science, and stroke epidemiology.
Research
Primary Care Research Group
The Primary Care Research Group is a diverse team consisting of clinical and non-clinical primary care team researchers
Stroke Research Group
We are a multidisciplinary group (epidemiologists, stroke physicians, GPs, social scientists, statisticians, health informaticians and health economists) focused on stroke and with a wider interest in vascular long-term conditions and analytics.
Digital Health
Digital Health Research Group is a multidisciplinary group of informaticians, clinicians, psychologists and computer scientists, researching the role of data and knowledge in medical research and practice.
Health Inequalities, Societies and Systems
Central to our research is understanding and tackling the systemic and intersecting drivers of disparities in health over the life course such as racism, gender, crime, precarious livelihoods, environmental pollution, and inaccessible health care. We work collaboratively across the School of Life Course and Population Sciences to strengthen the theoretical aspects of population health research.
Improving the lives of stroke survivors with data
We aim to improve the lives of stroke survivors through a programme of stakeholder engagement, data collection, analysis and modelling, and use in practice.
Project status: Ongoing
Centre for Data Futures
Bringing together interdisciplinary experts to focus on participatory infrastructure throughout the life of data-reliant tools.
Climate & sustainability researchers at King’s
King's researchers working across climate and sustainability
Equitable and Inclusive Patient and Public Involvement in Stroke Research (EquIPS)
EquIPS will coproduce tools for researchers that will support the participation of all stroke survivors, including those with severe stroke related impairments.
Project status: Ongoing
KingsCAT: Capture and Analysis Tool for Social Media Research at King’s College London
KingsCAT is an instance of the open source 4CAT: Capture and Analysis Toolkit set up to support interdisciplinary and collaborative social media research.
Project status: Ongoing
News
Study reveals urgent need for stroke prevention and care strategies in Sierra Leone
The research into common risk factors for stroke, type of stroke and outcomes of stroke in Sierra Leone uncovers a need for improved stroke care in the region
Events
Generative AI and the Future of Medical Care: an agenda for enquiry
The Centre for Data Futures and co-organisers discuss generative artificial intelligence challenges.
Please note: this event has passed.
MPH dissertation module
Research
Primary Care Research Group
The Primary Care Research Group is a diverse team consisting of clinical and non-clinical primary care team researchers
Stroke Research Group
We are a multidisciplinary group (epidemiologists, stroke physicians, GPs, social scientists, statisticians, health informaticians and health economists) focused on stroke and with a wider interest in vascular long-term conditions and analytics.
Digital Health
Digital Health Research Group is a multidisciplinary group of informaticians, clinicians, psychologists and computer scientists, researching the role of data and knowledge in medical research and practice.
Health Inequalities, Societies and Systems
Central to our research is understanding and tackling the systemic and intersecting drivers of disparities in health over the life course such as racism, gender, crime, precarious livelihoods, environmental pollution, and inaccessible health care. We work collaboratively across the School of Life Course and Population Sciences to strengthen the theoretical aspects of population health research.
Improving the lives of stroke survivors with data
We aim to improve the lives of stroke survivors through a programme of stakeholder engagement, data collection, analysis and modelling, and use in practice.
Project status: Ongoing
Centre for Data Futures
Bringing together interdisciplinary experts to focus on participatory infrastructure throughout the life of data-reliant tools.
Climate & sustainability researchers at King’s
King's researchers working across climate and sustainability
Equitable and Inclusive Patient and Public Involvement in Stroke Research (EquIPS)
EquIPS will coproduce tools for researchers that will support the participation of all stroke survivors, including those with severe stroke related impairments.
Project status: Ongoing
KingsCAT: Capture and Analysis Tool for Social Media Research at King’s College London
KingsCAT is an instance of the open source 4CAT: Capture and Analysis Toolkit set up to support interdisciplinary and collaborative social media research.
Project status: Ongoing
News
Study reveals urgent need for stroke prevention and care strategies in Sierra Leone
The research into common risk factors for stroke, type of stroke and outcomes of stroke in Sierra Leone uncovers a need for improved stroke care in the region
Events
Generative AI and the Future of Medical Care: an agenda for enquiry
The Centre for Data Futures and co-organisers discuss generative artificial intelligence challenges.
Please note: this event has passed.
MPH dissertation module