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Unsupervised learning to understand patterns of comorbidity in 633,330 patients diagnosed with osteoarthritis

Abstract:

With the advent of big data in healthcare, machine learning has rapidly gained popularity due to its potential to analyse large volumes of complex data from a variety of sources. Unsupervised learning can be used to mine data and discover patterns such as sub-groups within large patient populations. However challenges with implementation in large-scale datasets and interpretability of solutions in a real-world context remain. This work presents an application of unsupervised clustering techni...

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Publication status:
Published
Peer review status:
Peer reviewed

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Institution:
University of Oxford
Division:
MSD
Department:
NDORMS
Sub department:
Botnar Research Centre
Role:
Author
Publisher:
SciTePress
Host title:
Proceedings of the 15th International Joint Conference on Biomedical Engineering Systems and Technologies - BIOINFORMATICS
Volume:
3
Pages:
121-129
Publication date:
2022-02-24
Acceptance date:
2021-11-15
Event title:
BIOSTEC 2022
Event location:
Virtual Event
Event website:
https://biostec.scitevents.org/
Event start date:
2022-02-09
Event end date:
2022-02-11
DOI:
ISSN:
2184-4305
ISBN:
978-989-758-552-4
Language:
English
Keywords:
Pubs id:
1233280
Local pid:
pubs:1233280
Deposit date:
2022-01-25

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