Graph clustering system for text-based records in a clinical pathway

Takanori Yamashita, Naoya Onimura, Hidehisa Soejima, Naoki Nakashima, Sachio Hirokawa

研究成果: 書籍/レポート タイプへの寄稿会議への寄与

1 被引用数 (Scopus)

抄録

The progressive digitization of medical records has resulted in the accumulation of large amounts of data. Electronic medical data include structured numerical data and unstructured text data. Although text-based medical record processing has been researched, few studies contribute to medical practice. The analysis of unstructured text data can improve medical processes. Hence, this study presents a clustering approach for detecting typical patient's condition from text-based medical record of clinical pathway. In this approach, the sentences in a cluster are merged to generate a "sentence graph" of the cluster after classified feature word by Louvain method. An analysis of real text-based medical records indicates that sentence graphs can represent the medical treatment and patient's condition in a medical process. This method could help the standardization of text-based medical records and the recognition of feature medical processes for improving medical treatment.

本文言語英語
ホスト出版物のタイトルMEDINFO 2017
ホスト出版物のサブタイトルPrecision Healthcare through Informatics - Proceedings of the 16th World Congress on Medical and Health Informatics
編集者Adi V. Gundlapalli, Jaulent Marie-Christine, Zhao Dongsheng
出版社IOS Press BV
ページ649-652
ページ数4
ISBN(電子版)9781614998297
DOI
出版ステータス出版済み - 2017
イベント16th World Congress of Medical and Health Informatics: Precision Healthcare through Informatics, MedInfo 2017 - Hangzhou, 中国
継続期間: 8月 21 20178月 25 2017

出版物シリーズ

名前Studies in Health Technology and Informatics
245
ISSN(印刷版)0926-9630
ISSN(電子版)1879-8365

その他

その他16th World Congress of Medical and Health Informatics: Precision Healthcare through Informatics, MedInfo 2017
国/地域中国
CityHangzhou
Period8/21/178/25/17

!!!All Science Journal Classification (ASJC) codes

  • 生体医工学
  • 健康情報学
  • 健康情報管理

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