Analysis of medical care expenditure by Japanese prefecture using fuzzy robust regression model

Yoshiyuki Yabuuchi; Takayuki Kawaura; Junzo Watada

doi:10.3233/978-1-61499-474-9-400

Analysis of medical care expenditure by Japanese prefecture using fuzzy robust regression model

Yoshiyuki Yabuuchi, Takayuki Kawaura, Junzo Watada

研究成果: Conference contribution

1 被引用数 (Scopus)

抄録

In 2012, 15.13% of the total fiscal medical care expenditure was for lifestyle-related health care costs, which was approximately 179 billion yen. Lifestyle-related diseases are not only the biggest factor in reducing healthy life expectancy but also have the most significant impact on the national medical care expenditure. In addition, lifestyle-related diseases can be prevented by moderate daily exercise, a well-balanced diet, and not smoking. Our fuzzy robust regression model is a controllable model describing a target system. Therefore, our model is used to analyze the relation between medical care expenditure and selected lifestyle factors.

本文言語	English
ホスト出版物のタイトル	Studies in Health Technology and Informatics
出版社	IOS Press
ページ	400-409
ページ数	10
巻	207
ISBN（印刷版）	9781614994732
DOI	https://doi.org/10.3233/978-1-61499-474-9-400
出版ステータス	Published - 2014
イベント	2nd KES International Conference on Innovation in Medicine and Healthcare, InMed 2014 - San Sebastian 継続期間: 2014 7 9 → 2014 7 11

Other

Other	2nd KES International Conference on Innovation in Medicine and Healthcare, InMed 2014
City	San Sebastian
Period	14/7/9 → 14/7/11

ASJC Scopus subject areas

生体医工学
健康情報学
健康情報管理

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10.3233/978-1-61499-474-9-400

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引用スタイル

Yabuuchi, Y, Kawaura, T & Watada, J 2014, Analysis of medical care expenditure by Japanese prefecture using fuzzy robust regression model. in Studies in Health Technology and Informatics. vol. 207, IOS Press, pp. 400-409, 2nd KES International Conference on Innovation in Medicine and Healthcare, InMed 2014, San Sebastian, 14/7/9. https://doi.org/10.3233/978-1-61499-474-9-400

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Analysis of medical care expenditure by Japanese prefecture using fuzzy robust regression model

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