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- 後藤 哲史
- 帝京平成大学 健康メディカル学部
書誌事項
- タイトル別名
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- A Hierarchical Neural Network Model for Japanese Toward Detecting Mild Cognitive Impairment
抄録
<p>We found that some signs of Mild Cognitive Impairment (MCI) might be presented in a structure of a sentence and a relation between sentences talked by a man, and develop a neural network model which has an analogy with the hierarchical structure of speakers, tpoics, sentences and words in Japanese. We build our model based on 2-layered bi-directional LSTM, corresponding to words-sentences and sentences-topics hierarchy. As a layer corresponding to speakers, we use a linear classifier with self-attention. The test result shows a largely improved AUC, compared with our another test by using the normal 2-layered bi-directional LSTM with TBPTT. The result also indicates that there are some characteristic patterns in a talk by an elderly person with MCI. We classify the character vectors of topics generated from our model through learning into clusters whose number is 1/10 of the number of persons in our data. Since these clusters have almost less than 10% or more than 90% rate of positive share, we conclude that we can develop a screening method based on a talk in Japanese by an elderly person in the near future.</p>
収録刊行物
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- 電気学会論文誌C(電子・情報・システム部門誌)
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電気学会論文誌C(電子・情報・システム部門誌) 143 (4), 465-470, 2023-04-01
一般社団法人 電気学会
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キーワード
詳細情報 詳細情報について
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- CRID
- 1390014183322936064
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- ISSN
- 13488155
- 03854221
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- 本文言語コード
- ja
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- データソース種別
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- JaLC
- Crossref
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- 抄録ライセンスフラグ
- 使用不可