Abstract
In this chapter, biostatistics data mining methods applied in Asthma will be introduced into four frameworks: descriptive and explorative statistics, supervised data mining, unsupervised data mining, and time series analyses.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Chen K, et al. The effects of air pollution on asthma hospital admissions in Adelaide, South Australia, 2003–2013: time-series and casecrossover analyses. Clin Exp Allergy. 2016;46(11):1416–30. [Pubmed:27513706]
Li S, et al. Association of daily asthma emergency department visits and hospital admissions with ambient air pollutants among the pediatric Medicaid population in Detroit: time-series and time-stratified case-crossover analyses with threshold effects. Environ Res. 2011;111(8):1137–47. [Pubmed:21764049]
Michell TM. Machine learning. New York: McGraw-Hill; 1997. [ISBN: 9780070428072]
Cortes C, Vapnik V. Support-vector networks. Mach Learn. 1995;20(3):273–93. https://link.springer.com/content/pdf/10.1007%2FBF00994018.pdf
Metting, E.I., et al., Development of a diagnostic decision tree for obstructive pulmonary diseases based on real-life data. ERJ Open Res, 2016;2(1). [Pubmed: 5005160]
Zhang J, et al. Identifying ion channel genes related to cardiomyopathy using a novel decision forest strategy. Mol Biosyst. 2014;10(9):2407–14. [Pubmed: 24977958]
G, R. CHAID and earlier supervised tree methods. 2010. www.unige.ch/ses/metri/cahiers/2010_02.pdf
Williams Checkley MPD, Klawitter J, Romero KM, et al. Identifying biomarkers for asthma diagnosis using targeted metabolomics approaches. Respir Med. 2017;121:59–66. [Pubmed:27888993]
Pennington AF, et al. Exposure to mobile source air pollution in early life and childhood asthma incidence: the Kaiser Air Pollution and Pediatric Asthma Study. Epidemiology. 2017;29(1):22–30. [Pubmed:28926373]
Tan P, Introduction to data mining. Addison-Wesley Comanin Book Site 2006. http://www-users.cs.umn.edu/~kumar/dmbook/index.php. [ISBN:978-0321321367]
Rokach L, Maimon O. “Clustering methods.” Data mining and knowledge discovery handbook. Springer US, 2005. p. 321–352. [ISBN:978-0-387-25465-4]
Hartigan JA, Wong MA, Algorithm AS. 136: a K-means clustering algorithm. J R Stat Soc: Ser C Appl Stat. 1979;28(1):100–8. [ISBN:978-0-387-25465-4]
Kohonen T, Honkela T. Kohonen network. Scholarpedia, 2007
Ciampi A, Lechevallier Y. Clustering large, multi-level data sets: an approach based on Kohonen self organizing maps, in D.A. Zighed Springer LNCS (LNAI), 2000;1910:353–8.[ISBN:0302-9743]
Dunn JC. A fuzzy relative of the ISODATA process and its use in detecting compact well-separated clusters. J Cybern. 1973;3(3)(0022–0280): 32–57. https://doi.org/10.1080/01969727308546046
Bezdek JC. Pattern recognition with fuzzy objective function algorithms. New York: Plenum Press; 1981. (0-306-40671-3). [ISBN:978-1-4757-0450-1]
Hirai K, et al. A clustering approach to identify and characterize the asthma and chronic obstructive pulmonary disease overlap phenotype. Clin Exp Allergy. 2017;47(11):1374–82. [Pubmed:28658564]
Toti G, et al. Analysis of correlation between pediatric asthma exacerbation and exposure to pollutant mixtures with association rule mining. Artif Intell Med. 2016;74:44–52. [Pubmed:27964802]
Imdadullah, “Time Series Analysis”. Basic Statistics and Data Analysis. itfeature.com, 2014
Osborne NJ, et al. Pollen exposure and hospitalization due to asthma exacerbations: daily time series in a European city. Int J Biometeorol. 2017;61(10):1837–48. [Pubmed:28500390]
Brown K, et al. Improving timeliness for acute asthma care for paediatric ED patients using a nurse driven intervention: an interrupted time series analysis. BMJ Qual Improv Rep. 2016;5(1.) [Pubmed: 5223673]
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer Nature Singapore Pte Ltd.
About this chapter
Cite this chapter
Zhang, J. (2018). Biostatistics, Data Mining and Computational Modeling. In: Wang, X., Chen, Z. (eds) Genomic Approach to Asthma. Translational Bioinformatics, vol 12. Springer, Singapore. https://doi.org/10.1007/978-981-10-8764-6_15
Download citation
DOI: https://doi.org/10.1007/978-981-10-8764-6_15
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-10-8763-9
Online ISBN: 978-981-10-8764-6
eBook Packages: Biomedical and Life SciencesBiomedical and Life Sciences (R0)