Supervised deep learning with vision transformer predicts delirium using limited lead EEG
Supervised deep learning with vision transformer predicts delirium using limited lead EEG
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London: Nature Publishing Group UK
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English
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London: Nature Publishing Group UK
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As many as 80% of critically ill patients develop delirium increasing the need for institutionalization and higher morbidity and mortality. Clinicians detect less than 40% of delirium when using a validated screening tool. EEG is the criterion standard but is resource intensive thus not feasible for widespread delirium monitoring. This study evalua...
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Supervised deep learning with vision transformer predicts delirium using limited lead EEG
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TN_cdi_doaj_primary_oai_doaj_org_article_9e50704f72194f45a856903f6e8e30cd
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https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_9e50704f72194f45a856903f6e8e30cd
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ISSN
2045-2322
E-ISSN
2045-2322
DOI
10.1038/s41598-023-35004-y
