The prediction models of anaphylactic disease

Investigating the effect of common allergens on allergic disease is very important for human health. In this paper, we firstly propose the models for predicting the relationship between 39 common allergens and total IgE level. The total IgE level is utilized to evaluate the order of severity for all...

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Main Authors:	Changwei Wu, Pong Lu, Fang Xu, Jizhong Duan, Xiao Hua, Mohammad Shabaz
Format:	Article
Language:	English
Published:	Elsevier 2021-01-01
Series:	Informatics in Medicine Unlocked
Subjects:	IgE Allergic disease Allergen Neural network Linear fitting
Online Access:	http://www.sciencedirect.com/science/article/pii/S2352914821000253

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record_format	Article
spelling	doaj-8f574ea4b2794a36bf6b54383d6340f02021-06-19T04:54:57ZengElsevierInformatics in Medicine Unlocked2352-91482021-01-0124100535The prediction models of anaphylactic diseaseChangwei Wu0Pong Lu1Fang Xu2Jizhong Duan3Xiao Hua4Mohammad Shabaz5Capital Medical University, ChinaCapital Medical University, ChinaTianjin University, China; Corresponding author.Kunming University of Science and Technology, ChinaTsinghua University, ChinaLovely Professional University, IndiaInvestigating the effect of common allergens on allergic disease is very important for human health. In this paper, we firstly propose the models for predicting the relationship between 39 common allergens and total IgE level. The total IgE level is utilized to evaluate the order of severity for allergic disease. In particular, we employ the linear fitting method and neural network based method to obtain the models with high prediction accuracy. The feasibility of the proposed models can be confirmed by testing two other independent data sets from hospital diagnosis record. Additionally, we obtain some useful medical conclusions.http://www.sciencedirect.com/science/article/pii/S2352914821000253IgEAllergic diseaseAllergenNeural networkLinear fitting
collection	DOAJ
language	English
format	Article
sources	DOAJ
author	Changwei Wu Pong Lu Fang Xu Jizhong Duan Xiao Hua Mohammad Shabaz
spellingShingle	Changwei Wu Pong Lu Fang Xu Jizhong Duan Xiao Hua Mohammad Shabaz The prediction models of anaphylactic disease Informatics in Medicine Unlocked IgE Allergic disease Allergen Neural network Linear fitting
author_facet	Changwei Wu Pong Lu Fang Xu Jizhong Duan Xiao Hua Mohammad Shabaz
author_sort	Changwei Wu
title	The prediction models of anaphylactic disease
title_short	The prediction models of anaphylactic disease
title_full	The prediction models of anaphylactic disease
title_fullStr	The prediction models of anaphylactic disease
title_full_unstemmed	The prediction models of anaphylactic disease
title_sort	prediction models of anaphylactic disease
publisher	Elsevier
series	Informatics in Medicine Unlocked
issn	2352-9148
publishDate	2021-01-01
description	Investigating the effect of common allergens on allergic disease is very important for human health. In this paper, we firstly propose the models for predicting the relationship between 39 common allergens and total IgE level. The total IgE level is utilized to evaluate the order of severity for allergic disease. In particular, we employ the linear fitting method and neural network based method to obtain the models with high prediction accuracy. The feasibility of the proposed models can be confirmed by testing two other independent data sets from hospital diagnosis record. Additionally, we obtain some useful medical conclusions.
topic	IgE Allergic disease Allergen Neural network Linear fitting
url	http://www.sciencedirect.com/science/article/pii/S2352914821000253
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The prediction models of anaphylactic disease

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