Presentation 2003/3/7
Mining Hepatitis Data with Temporal Abstraction
Tu Bao Ho, Nguyen Trong Dung, Saori Kawasaki, Nguyen Due Dung,
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Abstract(in English) The hepatitis temporal database collected at Chiba university hospital during 1982-2001 was recently given to challenge the KDD research. The database is large where each patient corresponds to 983 tests as sequences of values with different lengths and irregular time-stamp points. This paper presents a temporal abstraction approach to mining knowledge from this hepatitis database. Exploiting hepatitis background knowledge and data analysis, we introduce methods for charactering short-term changed and long-term changed tests. The transformed data allows us to apply different machine learning methods for finding knowledge part of which is considered as new and interesting by medical doctors.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) Hepatitis / Temporal Abstraction / Change of State / Base State / Peak
Paper # AI2002-79
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Committee AI
Conference Date 2003/3/7(1days)
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Registration To Artificial Intelligence and Knowledge-Based Processing (AI)
Language ENG
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Mining Hepatitis Data with Temporal Abstraction
Sub Title (in English)
Keyword(1) Hepatitis
Keyword(2) Temporal Abstraction
Keyword(3) Change of State
Keyword(4) Base State
Keyword(5) Peak
1st Author's Name Tu Bao Ho
1st Author's Affiliation Japan Advancesd Institute of Science and Technology()
2nd Author's Name Nguyen Trong Dung
2nd Author's Affiliation Japan Advancesd Institute of Science and Technology
3rd Author's Name Saori Kawasaki
3rd Author's Affiliation Japan Advancesd Institute of Science and Technology
4th Author's Name Nguyen Due Dung
4th Author's Affiliation Japan Advancesd Institute of Science and Technology
Date 2003/3/7
Paper # AI2002-79
Volume (vol) vol.102
Number (no) 710
Page pp.pp.-
#Pages 6
Date of Issue