Tracking trajectories of multiple long-term conditions using dynamic patient-cluster associations-Reference-Cited by-同舟云学术

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Tracking trajectories of multiple long-term conditions using dynamic patient-cluster associations

Published:2022-12-17 Issue: Volume: Page:
ISSN:
Container-title:2022 IEEE International Conference on Big Data (Big Data)
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Author:

Kremer Ron¹,Raza Syed Mohib¹,Eto Fabiola²,Casement John³,Atallah Christian³,Finer Sarah²,Lendrem Dennis⁴,Barnes Michael⁵,Reynolds Nick J⁴,Missier Paolo¹

Affiliation:

1. Newcastle University,School of Computing,Newcastle upon Tyne,UK

2. Queen Mary University of London,Wolfson Institute of Population Health,London,UK

3. Newcastle University,Bioinformatics Support Unit,Newcastle upon Tyne,UK

4. Newcastle University,Faculty of Medical Sciences,Newcastle upon Tyne,UK

5. Queen Mary University of London,Centre For Translational Bioinformatics,London,UK

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10020192/10020156/10021034.pdf?arnumber=10021034

Reference32 articles.

1. Patterns of Multimorbidity in Middle-Aged and Older Adults: An Analysis of the UK Biobank Data

3. Multimorbidity patterns in the elderly: a prospective cohort study with cluster analysis

4. Multimorbidity and co-morbidity in atrial fibrillation and effects on survival: findings from UK Biobank cohort

5. Examining variation in the measurement of multimorbidity in research: a systematic review of 566 studies

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