title: Case-based retrieval framework for gene expression data.
abstract: BACKGROUND
  The process of retrieving similar cases in a case-based reasoning system is considered a big challenge for gene expression data sets. The huge number of gene expression values generated by microarray technology leads to complex data sets and similarity measures for high-dimensional data are problematic. Hence, gene expression similarity measurements require numerous machine-learning and data-mining techniques, such as feature selection and dimensionality reduction, to be incorporated into the retrieval process.
  
  
  METHODS
  This article proposes a case-based retrieval framework that uses a k-nearest-neighbor classifier with a weighted-feature-based similarity to retrieve previously treated patients based on their gene expression profiles.
  
  
  RESULTS
  The herein-proposed methodology is validated on several data sets: a childhood leukemia data set collected from The Children's Hospital at Westmead, as well as the Colon cancer, the National Cancer Institute (NCI), and the Prostate cancer data sets. Results obtained by the proposed framework in retrieving patients of the data sets who are similar to new patients are as follows: 96% accuracy on the childhood leukemia data set, 95% on the NCI data set, 93% on the Colon cancer data set, and 98% on the Prostate cancer data set.
  
  
  CONCLUSIONS
  The designed case-based retrieval framework is an appropriate choice for retrieving previous patients who are similar to a new patient, on the basis of their gene expression data, for better diagnosis and treatment of childhood leukemia. Moreover, this framework can be applied to other gene expression data sets using some or all of its steps.
authors: Center for Quantum Computation and Intelligent Systems, Faculty of Engineering and Information Technology, University of Technology Sydney, Broadway, New South Wales, Australia.
authors: Ali
authors: A
authors: Anaissi
authors: Center for Quantum Computation and Intelligent Systems, Faculty of Engineering and Information Technology, University of Technology Sydney, Broadway, New South Wales, Australia.
authors: Madhu
authors: M
authors: Goyal
authors: The Tumour Bank, Children's Cancer Research Unit, The Children's Hospital at Westmead, Westmead, New South Wales, Australia.
authors: Daniel R
authors: DR
authors: Catchpoole
authors: Center for Quantum Computation and Intelligent Systems, Faculty of Engineering and Information Technology, University of Technology Sydney, Broadway, New South Wales, Australia.
authors: Ali
authors: A
authors: Braytee
authors: Center for Quantum Computation and Intelligent Systems, Faculty of Engineering and Information Technology, University of Technology Sydney, Broadway, New South Wales, Australia.
authors: Paul J
authors: PJ
authors: Kennedy
keywords: case base reasoning; data mining; dimensionality reduction; feature weighting; gene expression; machine learning