The association forecasting of 13 variants within seven asthma susceptibility genes on 3 serum IgE groups in Taiwanese population by integrating of adaptive neuro-fuzzy inference system (ANFIS) and classification analysis methods

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Title:	The association forecasting of 13 variants within seven asthma susceptibility genes on 3 serum IgE groups in Taiwanese population by integrating of adaptive neuro-fuzzy inference system (ANFIS) and classification analysis methods
Authors:	劉寶鈞;Wang, Cheng-Hang;Liu, Baw-Jhiune;Wu, Lawrence Shih-Hsin
Contributors:	資訊電機學院資訊工程學系
Keywords:	Asian people;Asthma;Asthma - classification;Asthma - diagnosis;Asthma - genetics;Child;Child, Preschool;Classification;Diagnosis, Differential;Female;Fuzzy Logic;Genetic Predisposition to Disease;Genetic Testing - methods;Genotype & phenotype;Health Informatics;Health Sciences;Humans;Immunoglobulin E - genetics;Immunoglobulins;Male;Medicine;Medicine & Public Health;Models, Biological;Neural networks;Original Paper;Pediatrics;Polymorphism, Single Nucleotide;Respiratory Function Tests;Statistics for Life Sciences;Taiwan
Date:	2012-02-01
Issue Date:	2026-04-23 14:10:01 (UTC+8)
Publisher:	Springer New York;Boston: Springer Science and Business Media LLC
Abstract:	摘要： Asthma is one of the most common chronic diseases in children. It is caused by complicated coactions between various genetic factors and environmental allergens. The study aims to integrate the concept of implementing adaptive neuro-fuzzy inference system (ANFIS) and classification analysis methods for forecasting the association of asthma susceptibility genes on 3 serum IgE groups. The ANFIS model was trained and tested with data sets obtained from 425 asthmatic subjects and 483 non-asthma subjects from the Taiwanese population. We assessed 13 single-nucleotide polymorphisms (SNPs) in seven well-known asthma susceptibility genes; firstly, the proposed ANFIS model learned to reduce input features from the 13 SNPs. And secondly, the classification will be used to classify the serum IgE groups from the simulated SNPs results. The performance of the ANFIS model, classification accuracies and the results confirmed that the integration of ANFIS and classified analysis has potential in association discovery. 其他題名： J Med Syst 出版者： Boston: Springer Science and Business Media LLC 出版日期： 2012-02-01 出處： Journal of Medical Systems, 2012-02, Vol.36 (1), p.175-185 資源來源： Healthcare Administration Database (ProQuest) 版權： Springer Science+Business Media, LLC 2010 版權： Springer Science+Business Media, LLC 2012 識別號： ISSN: 0148-5598 識別號： EISSN: 1573-689X 識別號： DOI: 10.1007/s10916-010-9457-4 識別號： PMID: 20703737
Appears in Collections:	[Department of Computer Science and information Engineering] journal & Dissertation

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