Development and Evaluation of a Machine Learning Recursive Partitioning Decision Tree Algorithm to Optimize Urinalysis Parameters to Predict Urine Culture Positivity

PittUDT, a recursive partitioning decision tree algorithm for predicting urine culture (UC) positivity based on macroscopic and microscopic urinalysis (UA) parameters, may significantly decrease the number of unnecessary UC. The reflex algorithm derivation included 38,361 paired UA and UC cases; the...

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Vydané v:	bioRxiv
Hlavní autori:	Seheult, Jansen N, Stram, Michelle N, Contis, Lydia, Pontzer, Raymond E, Hardy, Stephanie, Baxter, Carla M, Ondras, Michael, Wertz, William, Kip, Paula L, Snyder, Graham M, Pasculle, A William
Médium:	Paper
Jazyk:	English
Vydavateľské údaje:	Cold Spring Harbor Cold Spring Harbor Laboratory Press 11.03.2023 Cold Spring Harbor Laboratory
Vydanie:	1.1
Predmet:	Algorithms Decision trees Feasibility studies Learning algorithms Machine learning Microbiology Urinalysis Urine reflex protocol PittUDT algorithm machine learning receiver operating characteristic
ISSN:	2692-8205, 2692-8205
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