K-Means Clustering for Asthma Endotypes
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http://www.who.int/respiratory/asthma/en/:referenced on7th December 2017.
Somayeh Akhavan Darabi et al. Case-Based-Reasoning System for Feature Selection and Diagnosing Disease; Case Study: Asthma. Innovative Systems Design and Engineering www.iiste.org, Vol.5, No.5, 2014:pp.43-59.
Wendy C. Moore et al. Identification of Asthma Phenotypes Using Cluster Analysis in the Severe Asthma Research Program. American Journal of Respiratory and Critical Care Medicine. 181(4). Feb 15 2010: pp.315–323.
Matea Deliu et al. Identification of Asthma Subtypes Using Clustering Methodologies. Pulmonary Therapy Vol.2. Issue.1. 2016:pp.19–41.
Keisuke Tsukioka et al. Phenotypic analysis of asthma in Japanese athletes. Allergology International.2017:pp.1-7.
Pinja Ilmarinen et al. Cluster Analysis on Longitudinal Data of Patients with Adult-Onset Asthma. Journal of Allergy and Clinical Immunology Practjuly/August 2017:pp. 967-978.
Wei Wu et al. Unsupervised Phenotyping of Severe Asthma Research Program participants using expanded lung data. Journal of Allergy and Clinical Immunology. 133(5). May 2014:pp.1280-1288.
Mattia C. F. Prosperi et al. Challenges in Identifying Asthma Subgroups Using Unsupervised Statistical Learning Techniques. American Journal of Respiratory and Critical Care Medicine.188 (11).2013:pp.1303-1312.
Pranab Haldar et al. Cluster Analysis and Clinical Asthma Phenotypes. American Journal of Respiratory and Critical Care Medicine. 178(3). August 2008:pp.218-224.
Loza MJ et al. Validated and Longitudinally Stable Asthma Phenotypes based on cluster Analysis of the ADEPT study. Respiratory Research.2016: pp.
Arnaud Bourdin et al. Prognostic value of cluster analysis of severe asthma phenotypes. Journal of Allergy and Clinical Immunology. Vol 134. Issue 5.November 2014: pp. 1043-1050.
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