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“School of Cognitive Sciences”

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Paper   IPM / Cognitive Sciences / 15898
School of Cognitive Sciences
  Title:   Classifying Pediatric Central Nervous System Tumors through near Optimal Feature Selection and Mutual Information: A Single Center Cohort
  Author(s): 
1. 
  Status:   Published
  Journal: Middle East Journal of Cancer
  Vol.:  4
  Year:  2013
  Pages:   153-162
  Supported by:  IPM
  Abstract:
Background: Labeling, gathering mutual information, clustering and classification of central nervous system tumors may assist in predicting not only distinct diagnoses based on tumor-specific features but also prognosis. This study evaluates the epidemi- ological features of central nervous system tumors in children who referred to Mahak’s Pediatric Cancer Treatment and Research Center in Tehran, Iran.Methods: This cohort (convenience sample) study comprised 198 children (≤15 years old) with central nervous system tumors who referred to Mahak's Pediatric Cancer Treatment and Research Center from 2007 to 2010. In addition to the descriptive analyses on epidemiological features and mutual information, we used the Least Squares Support Vector Machines method in MATLAB software to propose a preliminary predictive model of pediatric central nervous system tumor feature-label analysis.Results:Of patients, there were 63.1

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