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Mining Hepatitis Data with Temporal Abstraction
https://ipsj.ixsq.nii.ac.jp/records/50442
https://ipsj.ixsq.nii.ac.jp/records/50442f58c7eeb-0b61-42c9-b90e-69b57452b96d
名前 / ファイル | ライセンス | アクション |
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Copyright (c) 2003 by the Information Processing Society of Japan
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オープンアクセス |
Item type | SIG Technical Reports(1) | |||||||
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公開日 | 2003-03-13 | |||||||
タイトル | ||||||||
タイトル | Mining Hepatitis Data with Temporal Abstraction | |||||||
タイトル | ||||||||
言語 | en | |||||||
タイトル | Mining Hepatitis Data with Temporal Abstraction | |||||||
言語 | ||||||||
言語 | jpn | |||||||
資源タイプ | ||||||||
資源タイプ識別子 | http://purl.org/coar/resource_type/c_18gh | |||||||
資源タイプ | technical report | |||||||
著者所属 | ||||||||
Japan Advancesd Institute of Science and Technology | ||||||||
著者所属 | ||||||||
Japan Advancesd Institute of Science and Technology | ||||||||
著者所属 | ||||||||
Japan Advancesd Institute of Science and Technology | ||||||||
著者所属 | ||||||||
Japan Advancesd Institute of Science and Technology | ||||||||
著者所属(英) | ||||||||
en | ||||||||
Japan Advancesd Institute of Science and Technology | ||||||||
著者所属(英) | ||||||||
en | ||||||||
Japan Advancesd Institute of Science and Technology | ||||||||
著者所属(英) | ||||||||
en | ||||||||
Japan Advancesd Institute of Science and Technology | ||||||||
著者所属(英) | ||||||||
en | ||||||||
Japan Advancesd Institute of Science and Technology | ||||||||
著者名 |
TuBaoHo
× TuBaoHo
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著者名(英) |
Tu, BaoHo
× Tu, BaoHo
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論文抄録 | ||||||||
内容記述タイプ | Other | |||||||
内容記述 | The hepatitis temporal database collected at Chiba University gospital 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 mining knowledge from this hepatitis database. Exploiting hepatitis background knowledge and data analysis we introduce method for charactering short-term changed and long-term changed tests. The transformed data allows us to apply different machine learning methods for finding knowledge of part of which is considered as new and interesting by medical doctors. | |||||||
論文抄録(英) | ||||||||
内容記述タイプ | Other | |||||||
内容記述 | The hepatitis temporal database collected at Chiba University gospital 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 mining knowledge from this hepatitis database. Exploiting hepatitis background knowledge and data analysis, we introduce method for charactering short-term changed and long-term changed tests. The transformed data allows us to apply different machine learning methods for finding knowledge of part of which is considered as new and interesting by medical doctors. | |||||||
書誌レコードID | ||||||||
収録物識別子タイプ | NCID | |||||||
収録物識別子 | AA11135936 | |||||||
書誌情報 |
情報処理学会研究報告知能と複雑系(ICS) 巻 2003, 号 30(2002-ICS-132), p. 105-110, 発行日 2003-03-13 |
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Notice | ||||||||
SIG Technical Reports are nonrefereed and hence may later appear in any journals, conferences, symposia, etc. | ||||||||
出版者 | ||||||||
言語 | ja | |||||||
出版者 | 情報処理学会 |