Speech-based dementia classification for FTLD diagnosis support

Shunya Hanai, Shohei Kato, Koichi Sakaguchi, Takuto Sakuma, Reiko Ohdake, Michihito Masuda, Hirohisa Watanabe

研究成果: 書籍/レポート タイプへの寄稿会議への寄与

2 被引用数 (Scopus)

抄録

This paper proposes a screening system to automatically detect a Frontotemporal Lobar Degeneration (FTLD) and support a diagnosis of a general practitioner. Dementia results from a variety of diseases that primarily or secondarily affect the brain. It is important to diagnose an underlying disease correctly. We have been investigating FTLD, which is one of diseases. We took into account the specific symptoms, used speech features to classify FTLD, Alzheimer’s disease (AD) and healthy control (HC). We confirmed that our method can classify three groups with accuracy of 0.84 and macro F-measure of 0.79. We also showed the effectiveness of linguistic features in FTLD detection.

本文言語英語
ホスト出版物のタイトルLifeTech 2021 - 2021 IEEE 3rd Global Conference on Life Sciences and Technologies
出版社Institute of Electrical and Electronics Engineers Inc.
ページ344-346
ページ数3
ISBN(電子版)9781665418751
DOI
出版ステータス出版済み - 09-03-2021
イベント3rd IEEE Global Conference on Life Sciences and Technologies, LifeTech 2021 - Nara, 日本
継続期間: 09-03-202111-03-2021

出版物シリーズ

名前LifeTech 2021 - 2021 IEEE 3rd Global Conference on Life Sciences and Technologies

会議

会議3rd IEEE Global Conference on Life Sciences and Technologies, LifeTech 2021
国/地域日本
CityNara
Period09-03-2111-03-21

All Science Journal Classification (ASJC) codes

  • 生体医工学
  • 健康情報学
  • 健康(社会科学)
  • 生化学
  • 人工知能
  • コンピュータ サイエンスの応用

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