Development, Evaluation, and Multisite Deployment of a Machine Learning Decision Tree Algorithm To Optimize Urinalysis Parameters for Predicting Urine Culture Positivity

PittUDT, a recursive partitioning decision tree algorithm for predicting urine culture (UC) positivity based on macroscopic and microscopic urinalysis (UA) parameters, was developed in support of a broader system-wide diagnostic stewardship initiative to increase appropriateness of UC testing. Refle...

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Vydané v:	Journal of clinical microbiology Ročník 61; číslo 6; s. e0029123
Hlavní autori:	Seheult, Jansen N, Stram, Michelle N, Contis, Lydia, Pontzer, Raymond E, Hardy, Stephanie, Wertz, William, Baxter, Carla M, Ondras, Michael, Kip, Paula L, Snyder, Graham M, Pasculle, A William
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	United States 20.06.2023
Predmet:	Decision Trees Humans Machine Learning Middle Aged Retrospective Studies ROC Curve Urinalysis - methods Urinary Tract Infections - diagnosis Urinary Tract Infections - microbiology Urine - microbiology reflex protocol PittUDT algorithm machine learning receiver operating characteristic urine culture
ISSN:	1098-660X, 1098-660X
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