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Prediction of risk of urinary tract infection during hospital stay based on machine-learning

Started ‎02-08-2023 by
Modified ‎02-10-2023 by
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Published in Plos One, 16(3)

Abstract:

Healthcare associated infections (HAI) are a major burden for the healthcare system and associated with prolonged hospital stay, increased morbidity, mortality and costs. Healthcare associated urinary tract infections (HA-UTI) accounts for about 20–30% of all HAI’s, and with the emergence of multi-resistant urinary tract pathogens, the total burden of HA-UTI will most likely increase. Article authors include SAS authors using SAS Software. 

 

Kjølseth Møller, J., Sørensen, M., Hardahl, C. (2021), Plos One, 16(3).

Prediction of risk of acquiring urinary tract infection during hospital stay based on machine-learni...

 

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