Using machine learning to extract cognitive status from the sleep EEG in progressing stages of dementia: defining interpretable and age-related features
Author:
Affiliation:
1. Mount Sinai Integrative Sleep Center, Division of Pulmonary, Critical Care, and Sleep Medicine, and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai , New York, NY , USA
Funder
Itamar Medical Ltd
Publisher
Oxford University Press (OUP)
Subject
Physiology (medical),Neurology (clinical)
Link
https://academic.oup.com/sleep/advance-article-pdf/doi/10.1093/sleep/zsac324/48907359/zsac324.pdf
Reference13 articles.
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2. Candidate mechanisms underlying the association between sleep-wake disruptions and Alzheimer’s disease;Cedernaes;Sleep Med Rev.,2017
3. Dementia detection from brain activity during sleep;Ye;Sleep,2023
4. Definitions, methods, and applications in interpretable machine learning.;Murdoch;Proc Natl Acad Sci U S A.,2019
5. Index of theta/alpha ratio of the quantitative electroencephalogram in Alzheimer’s disease: a case-control study;Fahimi;Acta Med Iran.,2017
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