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Open Access
Peer-reviewed
Research Article
A population-based study exploring phenotypic clusters and clinical outcomes in stroke using unsupervised machine learning approach
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Ralph K. Akyea ,
Contributed equally to this work with: Ralph K. Akyea, Stephen F. Weng, Nadeem Qureshi
Roles Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Resources, Visualization, Writing – original draft, Writing – review & editing
* E-mail: Ralph.Akyea1@nottingham.ac.uk
¶‡ These authors are joint senior authors on this work.
Affiliation PRISM Research Group, Centre for Academic Primary Care, School of Medicine, University of Nottingham, Nottingham, United Kingdom
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George Ntaios,
Roles Writing – review & editing
Affiliation Department of Internal Medicine, Faculty of Medicine, School of Health Sciences, University of Thessaly, Larissa, Greece
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Evangelos Kontopantelis,
Roles Writing – review & editing
Affiliations Division of Population Health, Health Services Research and Primary Care, School of Health Sciences, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre (MAHSC), The University of Manchester, Manchester, United Kingdom, Division of Informatics, Imaging and Data Sciences, School of Health Sciences, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre (MAHSC), The University of Manchester, Manchester, United Kingdom
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Georgios Georgiopoulos,
Roles Writing – review & editing
Affiliation School of Biomedical Engineering and Imaging Sciences, St Thomas Hospital, King’s College London, London, United Kingdom
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Daniele Soria,
Roles Writing – review & editing
Affiliation School of Computing, University of Kent, Canterbury, United Kingdom
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Folkert W. Asselbergs,
Roles Writing – review & editing
Affiliations Amsterdam University Medical Centers, Department of Cardiology, University of Amsterdam, Amsterdam, The Netherlands, Health Data Research UK and Institute of Health Informatics, University College London, London, United Kingdom
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Joe Kai,
Roles Funding acquisition, Writing – review & editing
Affiliation PRISM Research Group, Centre for Academic Primary Care, School of Medicine, University of Nottingham, Nottingham, United Kingdom
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Stephen F. Weng ,
Contributed equally to this work with: Ralph K. Akyea, Stephen F. Weng, Nadeem Qureshi
Roles Conceptualization, Funding acquisition, Methodology, Supervision, Writing – review & editing
¶‡ These authors are joint senior authors on this work.
Affiliation PRISM Research Group, Centre for Academic Primary Care, School of Medicine, University of Nottingham, Nottingham, United Kingdom
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Nadeem Qureshi
Contributed equally to this work with: Ralph K. Akyea, Stephen F. Weng, Nadeem Qureshi
Roles Conceptualization, Funding acquisition, Supervision, Writing – review & editing
¶‡ These authors are joint senior authors on this work.
Affiliation PRISM Research Group, Centre for Academic Primary Care, School of Medicine, University of Nottingham, Nottingham, United Kingdom
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A population-based study exploring phenotypic clusters and clinical outcomes in stroke using unsupervised machine learning approach
- Ralph K. Akyea,
- George Ntaios,
- Evangelos Kontopantelis,
- Georgios Georgiopoulos,
- Daniele Soria,
- Folkert W. Asselbergs,
- Joe Kai,
- Stephen F. Weng,
- Nadeem Qureshi
- Published: September 13, 2023
- https://doi.org/10.1371/journal.pdig.0000334