Instance-based classifiers applied to medical databases: Diagnosis and knowledge extraction
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摘要
ObjectiveThe aim of this paper is to study the feasibility and the performance of some classifier systems belonging to family of instance-based (IB) learning as second-opinion diagnostic tools and as tools for the knowledge extraction phase in the process of knowledge discovery in clinical databases.
论文关键词：Instance-based learning,Nearest-neighbour rule,Prototype methods,Bias-variance dilemma,Nosological diagnosis,Knowledge discovery in databases,Erythemato-squamous diseases,Diabetes mellitus,Single proton emission computed tomography
论文评审过程：Received 25 June 2009, Revised 20 March 2011, Accepted 18 April 2011, Available online 28 May 2011.
论文官网地址：https://doi.org/10.1016/j.artmed.2011.04.002
