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Predicting delirium and the effects of medications in hospitalized COVID-19 patients using machine learning: A retrospective study within the Korean Multidisciplinary Cohort for Delirium Prevention (KoMCoDe).

So Hee LeeHyun Jung HurSung Nyun KimJang Ho AhnDu Hyun RoArum HongHye Yoon ParkPyoeng Gyun ChoeBack KimHye Youn Park
Published in: Digital health (2024)
We developed and internally validated an ML model to predict delirium in COVID-19 inpatients. The model identified modifiable factors associated with the development of delirium and could be clinically useful for the prediction and prevention of delirium in COVID-19 inpatients.
Keyphrases
  • cardiac surgery
  • sars cov
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  • coronavirus disease
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  • respiratory syndrome coronavirus