Mining Hepatitis Data with Temporal Abstraction (文部科学省科学研究費特定領域研究「情報洪水時代におけるアクティブマイニングの実現」公開シンポジウム)

概要

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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.
一般社団法人情報処理学会の論文
2003-03-13