Presentation 2003/3/8
Active Mining from Plural Data Sources : A Study in Quest of Common Causal Models from Two Medical Test Data Sets
Masanori INADA, Takao TERANO,
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Abstract(in English) This paper employs interactive evolutionary computing techniques for an active mining task. In the task, we search for common causal models in two data sets from different medical databases. Because medical test data are incompatible among hospitals, it is difficult to merge plural data sets from different sources. We therefore formalize a simultaneous searching problem to get common causal models described by structural equation modeling for each data set. To acquire common causal models, we designed a mining system, which copes with the feature selection procedure with Evolutionary Computation techniques to interactively evolve offspring. In the procedure, a user will judge individuals subjectively or interactively in a human-in-a-loop manner. Experimental results on liver function test data show the effectiveness of the proposed method.
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Keyword(in English) Active Mining / Interactive Evolutionary Computing / Structural Equation Modeling / Liver Function Test Data
Paper # AI2002-91
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Committee AI
Conference Date 2003/3/8(1days)
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Registration To Artificial Intelligence and Knowledge-Based Processing (AI)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Active Mining from Plural Data Sources : A Study in Quest of Common Causal Models from Two Medical Test Data Sets
Sub Title (in English)
Keyword(1) Active Mining
Keyword(2) Interactive Evolutionary Computing
Keyword(3) Structural Equation Modeling
Keyword(4) Liver Function Test Data
1st Author's Name Masanori INADA
1st Author's Affiliation Department of Clinical Laboratory, Toranomon Hospital()
2nd Author's Name Takao TERANO
2nd Author's Affiliation Graduate School of Business Sciences, University of Tsukuba
Date 2003/3/8
Paper # AI2002-91
Volume (vol) vol.102
Number (no) 711
Page pp.pp.-
#Pages 6
Date of Issue