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

Journal of Medical Systems

Volumn 36, Issue 1, 2012, Pages 175-185

  Wang, Cheng Hang ^a   Liu, Baw Jhiune ^a   Wu, Lawrence Shih Hsin ^b  

^a YUAN ZE UNIVERSITY   (Taiwan)

^b TZU CHI UNIVERSITY   (Taiwan)

Author keywords

Adaptive neuro fuzzy inference system (ANFIS); Classify analysis; Fuzzy logic; Pediatric asthma; SNPs

Indexed keywords

IMMUNOGLOBULIN E;

ACCURACY; ADAPTIVE NEURO FUZZY INFERENCE SYSTEM; ARTICLE; ASTHMA; CHILD; FUZZY SYSTEM; GENETIC ASSOCIATION; GENETIC VARIABILITY; HUMAN; MAJOR CLINICAL STUDY; MEDICAL RECORD; PRESCHOOL CHILD; SCHOOL CHILD; SINGLE NUCLEOTIDE POLYMORPHISM; BIOLOGICAL MODEL; CLASSIFICATION; DIFFERENTIAL DIAGNOSIS; FEMALE; FUZZY LOGIC; GENETIC PREDISPOSITION; GENETIC SCREENING; GENETICS; LUNG FUNCTION TEST; MALE; METHODOLOGY; TAIWAN;

ASTHMA; CHILD; CHILD, PRESCHOOL; DIAGNOSIS, DIFFERENTIAL; FEMALE; FUZZY LOGIC; GENETIC PREDISPOSITION TO DISEASE; GENETIC TESTING; HUMANS; IMMUNOGLOBULIN E; MALE; MODELS, BIOLOGICAL; POLYMORPHISM, SINGLE NUCLEOTIDE; RESPIRATORY FUNCTION TESTS; TAIWAN;

EID: 84860229578     PISSN: 01485598     EISSN: 1573689X     Source Type: Journal    
DOI: 10.1007/s10916-010-9457-4     Document Type: Article

References (38)

1. Mobley, B. A., Schechter, E., Moore, W. E., McKee, P. A., and Eichner, J. E., Predictions of coronary artery stenosis by artificial neural network. Artif. Intell. Med. 18:187-203, 2000. (Pubitemid 30089528)
2. Miller, A. S., Blott, B. H., and Hames, T. K., Review of neural network applications in medical imaging and signal processing. Med. Biol. Eng. Comput. 30:449-464, 1992.
3. Übeyli, E. D., Usage of eigenvector methods to improve reliable classifier for Doppler ultrasound signals. Comput. Biol. Med. 38:5563-5573, 2008.
4. Übeyli, E. D., Comparison of different classification algorithms in clinical decision-making. Expert Syst. 24:117-131, 2007.
5. Übeyli, E. D., Detection of electrocardiogram beats using a fuzzy similarity index. Expert Syst. 24:287-296, 2007.
6. Übeyli, E. D., Combining neural network models for automated diagnostic systems. J. Med. Syst. 30:6483-6488, 2006.
7. Übeyli, E. D., Time-varying biomedical signals analysis with multiclass support vector machines employing Lyapunov exponents. Digit. Signal Process. 18:4646-4656, 2008.
8. Baxt, W. G., Use of an artificial neural network for data analysis in clinical decision making: The diagnosis of acute coronary occlusion. Neural Comput. 2:480-489, 1990.
9. Ergün, U., Serhatlioglu, S., Hardalac, F., and Guler, I., Classification of carotid artery stenosis of the patients with diabetes by neural network and logistic regression. Comput. Biol. Med. 34:389-405, 2004. (Pubitemid 38625608)
10. Güler, I., and Übeyli, E. D., Detection of ophthalmic artery stenosis by least-mean squares back propagation neural network. Comput. Biol. Med. 33:333-343, 2003. (Pubitemid 36638788)
11. Dubois, D., and Prade, H., An introduction to fuzzy systems. Clin. Chim. Acta 270:3-29, 1998. (Pubitemid 28254904)
12. Kuncheva, L. I., and Steimann, F., Fuzzy diagnosis. Art. Intell. Med. 16:121-128, 1999.
13. Nauck, D., and Kruse, R., Obtaining interpretable fuzzy classification rules from medical data. Art. Intell. Med. 16:149-169, 1999. (Pubitemid 29236497)
14. Güler, I., Hardalac, F., Ergün, U., and Baris-C, N., Application of FFT analyzed cardiac Doppler signals to fuzzy algorithm. Comput. Biol. Med. 32:435-444, 2002.
15. Güler, I., Hardalac, F., Ergün, U., and Baris-C, N., Classification of aorta Doppler signals using variable coded hierarchical genetic fuzzy system. Expert Syst. Appl. 26:321-333, 2004.
16. Andrews, R., Diederich, J., and Tickle, A., A survey and critique of techniques for extracting rules from trained artificial neural networks. Knowl. Base Syst. 8:373-389, 1995.
17. Mcgarry, K., Wermter, S., and Macintyre, J., The extraction and comparison of knowledge from local function networks. Int. J. Comput. Intell. Appl. 1:369-382, 2001.
18. Jang, J. S. R., ANFIS: Adaptive-network-based fuzzy inference system. IEEE Trans. Syst. Man Cybern. 23:3665-3685, 1993.
19. Usher, J., Campbell, D., Vohra, J., and Cameron, J., A fuzzy logic controlled classifier for use in implantable cardioverter defibrillators. Pacing Clin. Electrophysiol. 22:183-186, 1999. (Pubitemid 29066556)
20. Belal, S. Y., Taktak, A. F. G., Nevill, A. J., Spencer, S. A., Roden, D., and Bevan, S., Automatic detection of distorted plethysmogram pulses in neonates and pediatric patients using an adaptive network-based fuzzy inference system. Artif. Intell. Med. 24:149-165, 2002. (Pubitemid 34119149)
21. Virant-Klun, I., and Virant, J., Fuzzy logic alternative for analysis in the biomedical sciences. Comput. Biomed. Res. 32:305-321, 1999. (Pubitemid 29390397)
22. Masoli, M., Fabian, D., Holt, S., and Beasley, R., The global burden of asthma: Executive summary of GINA Dissemination Committee Report. Allergy 59:469-478, 2004. (Pubitemid 38580764)
23. Beasley, R., The burden of asthma with specific reference to the United States. J. Allergy Clin. Immunol. 109:S482-S489, 2002. (Pubitemid 34499500)
24. Bach, J. F., The effect of infections on susceptibility to autoimmune and allergic diseases. N. Engl. J. Med. 347:911-920, 2002.
25. Skadhauge, L. R., Christensen, K., Kyvik, K. O., and Sigsgaard, T., Genetic and environmental influence on asthma: A populationbased study of 11688 Danish twin pairs. Eur. Respir. J. 13:8-14, 1999. (Pubitemid 29079212)
26. Ober, C., and Hoffjan, S., Asthma genetics 2006: The long and winding road to gene discovery. Genes Immun. 7:95-100, 2006. (Pubitemid 43336051)
27. Anderson, G. G., and Cookson, W. O., Recent advanced in the genetics of allergy and asthma. Mol. Med. Today 5:264-273, 1999. (Pubitemid 29282465)
28. Blumenthal, M. M., What we know about the genetics of asthma at the beginning of the 21st century. Clin. Rev. Allergy Immunol. 22:11-31, 2002. (Pubitemid 34074777)
29. Holloway, J. W., Beghe, B., and Holgate, S. T., The genetic basis of atopic asthma. Clin. Exp. Allergy 29:1023-1032, 1999. (Pubitemid 29359418)
30. Huang, J. L., Asthma severity and genetics in Taiwan. J. Microbiol. Immunol. Infect. 38:158-163, 2005.
31. Burney, P. G., Luczynska, C., Chinn, S., and Jarvis, D., The European Community Respiratory Health Survey. Eur. Respir. J. 5:954-960, 1994. (Pubitemid 24153598)
32. Pearce, N., Sunyer, J., Cheng, S., Chinn, S., Bjorksten, B., Burr, M., Keil, U., Anderson, H. R., and Burney, P., Comparison of asthma prevalence in the ISAAC and the ECRHS. ISAAC Steering Committee and the European Community Respiratory Health Survey. International Study of Asthma and Allergies in Childhood. Eur. Respir. J. 16:420-426, 2000.
33. Beydon, N., Davis, S. D., Lombardi, E., Allen, J. L., Arets, H. G. M., Aurora, P., Bisgaard, H., Davis, G. M., Ducharme, F. M., Eigen, H., Gappa, M., Gaultier, C., Gustafsson, P. M., Hall, G. L., Hantos, Z., Healy, M. J. R., Jones, M. H., Klug, B., Carlsen, K. C. L., McKenzie, S. A., Marchal, F., Mayer, O. H., Merkus, P. J. F. M., Morris, M. G., Oostveen, E., Pillow, J. J., Seddon, P. C., Silverman, M., Sly, P. D., Stocks, J., Tepper, R. S., Vilozni, D., and Wilson, N. H., Behalf of the American Thoracic Society/European Respiratory Society Working Group on Infant and Young Children Pulmonary Function Testing. An official American Thoracic Society/European Respiratory Society Statement: Pulmonary function testing in preschool children. Am. J. Respir. Crit. Care Med. 175:1304-1345, 2007.
34. Terano, T., Asai, K., and Sugeno, M., Fuzzy systems theory and its applications. Academic, San Diego, 1992.
35. Mamdani, E. H., and Assilian, S., An experiment in linquistic synthesis with a fuzzy logic controller. Int. J. Man-Mach. Stud. 7:1-8, 1975.
36. Sugeno, M., and Kang, G. T., Structure identification of fuzzy model. Fuzzy Sets Syst. 28:15-33, 1988.
37. Leung, T. F., Tang, N. L. S., Chan, H. I. S., Li, A. M., Ha, G., Lam, C. W. K., and Fok, T. F., Distribution in allele frequencies of predisposition-to atopy genotypes in Chinese children. Pediatr. Pulmonol. 34:419-424, 2002. (Pubitemid 35375632)
38. Unoki, M., Furuta, S., Onouchi, Y., Watanabe, O., Doi, S., Fujiwara, H., Miyatake, A., Fujita, K., Tamari, M., and Nakamura, Y., Association studies of 33 single nucleotide polymorphisms (SNPs) in 29 candidate genes for bronchial asthma: Positive association a T294C polymorphism in the thromboxane A2 receptor gene. Hum. Genet. 106:440-446, 2000. (Pubitemid 30237512)