Interpretable machine learning for high-dimensional trajectories of aging health
Interpretable machine learning for high-dimensional trajectories of aging health
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Publisher
United States: Public Library of Science
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Language
English
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Publisher
United States: Public Library of Science
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Scope and Contents
Contents
We have built a computational model for individual aging trajectories of health and survival, which contains physical, functional, and biological variables, and is conditioned on demographic, lifestyle, and medical background information. We combine techniques of modern machine learning with an interpretable interaction network, where health variab...
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Full title
Interpretable machine learning for high-dimensional trajectories of aging health
Authors, Artists and Contributors
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TN_cdi_plos_journals_2762184219
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_plos_journals_2762184219
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ISSN
1553-7358,1553-734X
E-ISSN
1553-7358
DOI
10.1371/journal.pcbi.1009746
