Outlier detection of vital sign trajectories from COVID-19 patients
Outlier detection of vital sign trajectories from COVID-19 patients
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Ithaca: Cornell University Library, arXiv.org
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English
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Ithaca: Cornell University Library, arXiv.org
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In this work, we present a novel trajectory comparison algorithm to identify abnormal vital sign trends, with the aim of improving recognition of deteriorating health. There is growing interest in continuous wearable vital sign sensors for monitoring patients remotely at home. These monitors are usually coupled to an alerting system, which is trigg...
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Outlier detection of vital sign trajectories from COVID-19 patients
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TN_cdi_proquest_journals_2691251394
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https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_2691251394
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E-ISSN
2331-8422
