Identifying risk factors for Alzheimer's disease from multivariate longitudinal clinical data using...
Identifying risk factors for Alzheimer's disease from multivariate longitudinal clinical data using temporal pattern mining
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Publisher
England: BioMed Central Ltd
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Language
English
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Publisher
England: BioMed Central Ltd
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Contents
Patient data contain a wealth of information that could aid in understanding the onset and progression of disease. However, the task of modelling clinical data, which consist of multiple heterogeneous time series of different lengths, measured at different time intervals, is a complex one. A growing body of research has applied temporal pattern min...
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Full title
Identifying risk factors for Alzheimer's disease from multivariate longitudinal clinical data using temporal pattern mining
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TN_cdi_doaj_primary_oai_doaj_org_article_60be6a7c3d1f45aca219f58c3edfef39
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https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_60be6a7c3d1f45aca219f58c3edfef39
Other Identifiers
ISSN
1471-2105
E-ISSN
1471-2105
DOI
10.1186/s12859-024-06018-8
