Correction: A machine learning approach to predict intravenous immunoglobulin resistance in Kawasaki disease patients: A study based on a Southeast China population.

[This corrects the article DOI: 10.1371/journal.pone.0237321.].

Bibliographic Details
Main Authors:	Tengyang Wang, Guanghua Liu, Hongye Lin
Format:	Article
Language:	English
Published:	Public Library of Science (PLoS) 2021-01-01
Series:	PLoS ONE
Online Access:	https://doi.org/10.1371/journal.pone.0253675

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record_format	Article
spelling	doaj-e05eefed09fc4fd9ac672aba1ecd15d02021-07-04T04:30:13ZengPublic Library of Science (PLoS)PLoS ONE1932-62032021-01-01166e025367510.1371/journal.pone.0253675Correction: A machine learning approach to predict intravenous immunoglobulin resistance in Kawasaki disease patients: A study based on a Southeast China population.Tengyang WangGuanghua LiuHongye Lin[This corrects the article DOI: 10.1371/journal.pone.0237321.].https://doi.org/10.1371/journal.pone.0253675
collection	DOAJ
language	English
format	Article
sources	DOAJ
author	Tengyang Wang Guanghua Liu Hongye Lin
spellingShingle	Tengyang Wang Guanghua Liu Hongye Lin Correction: A machine learning approach to predict intravenous immunoglobulin resistance in Kawasaki disease patients: A study based on a Southeast China population. PLoS ONE
author_facet	Tengyang Wang Guanghua Liu Hongye Lin
author_sort	Tengyang Wang
title	Correction: A machine learning approach to predict intravenous immunoglobulin resistance in Kawasaki disease patients: A study based on a Southeast China population.
title_short	Correction: A machine learning approach to predict intravenous immunoglobulin resistance in Kawasaki disease patients: A study based on a Southeast China population.
title_full	Correction: A machine learning approach to predict intravenous immunoglobulin resistance in Kawasaki disease patients: A study based on a Southeast China population.
title_fullStr	Correction: A machine learning approach to predict intravenous immunoglobulin resistance in Kawasaki disease patients: A study based on a Southeast China population.
title_full_unstemmed	Correction: A machine learning approach to predict intravenous immunoglobulin resistance in Kawasaki disease patients: A study based on a Southeast China population.
title_sort	correction: a machine learning approach to predict intravenous immunoglobulin resistance in kawasaki disease patients: a study based on a southeast china population.
publisher	Public Library of Science (PLoS)
series	PLoS ONE
issn	1932-6203
publishDate	2021-01-01
description	[This corrects the article DOI: 10.1371/journal.pone.0237321.].
url	https://doi.org/10.1371/journal.pone.0253675
work_keys_str_mv	AT tengyangwang correctionamachinelearningapproachtopredictintravenousimmunoglobulinresistanceinkawasakidiseasepatientsastudybasedonasoutheastchinapopulation AT guanghualiu correctionamachinelearningapproachtopredictintravenousimmunoglobulinresistanceinkawasakidiseasepatientsastudybasedonasoutheastchinapopulation AT hongyelin correctionamachinelearningapproachtopredictintravenousimmunoglobulinresistanceinkawasakidiseasepatientsastudybasedonasoutheastchinapopulation
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Correction: A machine learning approach to predict intravenous immunoglobulin resistance in Kawasaki disease patients: A study based on a Southeast China population.

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