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Comparison between machine learning and logistic regression..:

Jee Soo Park (10532447) ; Dong Wook Kim (92904) ; Dongu Lee (11777999)...
https://figshare.com/articles/dataset/Comparison_between_machine_learning_and_logistic_regression_models_for_predicting_the_spontaneous_passage_of_ureteral_stones_/17106794. , 2021

Link: https://doi.org/10.1371/journal.pone.0260517.t004

RT Journal
T1 <Title>Comparison between machine learning and logistic regression models for predicting the spontaneous passage of ureteral stones</Title>

UL https://suche.suub.uni-bremen.de/peid=base-ftsmithonian:oai:figshare.com:article_17106794&Exemplar=1&LAN=DE
				
A1 Jee Soo Park (10532447)
A1 Dong Wook Kim (92904)
A1 Dongu Lee (11777999)
A1 Taeju Lee (3840478)
A1 Kyo Chul Koo (11778002)
A1 Woong Kyu Han (11778005)
A1 Byung Ha Chung (6692924)
A1 Kwang Suk Lee (11778008)
YR 2021
K1 Biochemistry
K1 Medicine
K1 Cell Biology
K1 Developmental Biology
K1 Infectious Diseases
K1 Biological Sciences not elsewhere classified
K1 receiver operating characteristic
K1 perform active treatment
K1 avoid unwanted complications
K1 first stone episode
K1 5 &# 8211
K1 using machine learning
K1 clinician determines whether
K1 unilateral ureteral stones
K1 machine learning
K1 ureteral stones
K1 stone opacity
K1 5 mm
K1 xlink ">
K1 underwent non
K1 september 2018
K1 prediction model
K1 logistic regression
K1 future studies
K1 emergency department
K1 august 2014
K1 7 %)
JF https://figshare.com/articles/dataset/Comparison_between_machine_learning_and_logistic_regression_models_for_predicting_the_spontaneous_passage_of_ureteral_stones_/17106794
LK http://dx.doi.org/https://doi.org/10.1371/journal.pone.0260517.t004
DO https://doi.org/10.1371/journal.pone.0260517.t004
SF ELIB - SuUB Bremen

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