The development of an electronic phenotyping algorithm for identifying rhabdomyolysis patients in the Mid-NEt database

Rieko Izukura; Tadashi Kandabashi; Yoshifumi Wakata; Chinatsu Nojiri; Yasunobu Nohara; Takanori Yamashita; Atsushi Takada; Jinsang Park; Yoshiaki Uyama; Naoki Nakashima

doi:10.3233/SHTI190503

The development of an electronic phenotyping algorithm for identifying rhabdomyolysis patients in the Mid-NEt database

Rieko Izukura, Tadashi Kandabashi, Yoshifumi Wakata, Chinatsu Nojiri, Yasunobu Nohara, Takanori Yamashita, Atsushi Takada, Jinsang Park, Yoshiaki Uyama, Naoki Nakashima

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

We aimed to develop rhabdomyolysis (RB) phenotyping algorithms using machine learning techniques and to create subphenotyping algorithms to identify RB patients who lack RB diagnosis. Two pattern algorithms, one with a focus on improving predictive value and one focused on improving sensitivity, were finally created and had a high area under the curve value of 0.846. Although we were unable to create subphenotyping algorithms, an attempt to detect unknown RB patients is important for epidemiological studies.

本文言語	英語
ホスト出版物のタイトル	MEDINFO 2019
ホスト出版物のサブタイトル	Health and Wellbeing e-Networks for All - Proceedings of the 17th World Congress on Medical and Health Informatics
編集者	Brigitte Seroussi, Lucila Ohno-Machado, Lucila Ohno-Machado, Brigitte Seroussi
出版社	IOS Press
ページ	1498-1499
ページ数	2
ISBN（電子版）	9781643680026
DOI	https://doi.org/10.3233/SHTI190503
出版ステータス	出版済み - 8月 21 2019
イベント	17th World Congress on Medical and Health Informatics, MEDINFO 2019 - Lyon, フランス継続期間: 8月 25 2019 → 8月 30 2019

出版物シリーズ

名前	Studies in Health Technology and Informatics
巻	264
ISSN（印刷版）	0926-9630
ISSN（電子版）	1879-8365

会議

会議	17th World Congress on Medical and Health Informatics, MEDINFO 2019
国/地域	フランス
City	Lyon
Period	8/25/19 → 8/30/19

!!!All Science Journal Classification (ASJC) codes

生体医工学
健康情報学
健康情報管理

文献へのアクセス

10.3233/SHTI190503

他のファイルとリンク

引用スタイル

Izukura, R., Kandabashi, T., Wakata, Y., Nojiri, C., Nohara, Y., Yamashita, T., Takada, A., Park, J., Uyama, Y., & Nakashima, N. (2019). The development of an electronic phenotyping algorithm for identifying rhabdomyolysis patients in the Mid-NEt database. In B. Seroussi, L. Ohno-Machado, L. Ohno-Machado, & B. Seroussi (Eds.), MEDINFO 2019: Health and Wellbeing e-Networks for All - Proceedings of the 17th World Congress on Medical and Health Informatics (pp. 1498-1499). (Studies in Health Technology and Informatics; Vol. 264). IOS Press. https://doi.org/10.3233/SHTI190503

The development of an electronic phenotyping algorithm for identifying rhabdomyolysis patients in the Mid-NEt database. / Izukura, Rieko; Kandabashi, Tadashi; Wakata, Yoshifumi その他.
MEDINFO 2019: Health and Wellbeing e-Networks for All - Proceedings of the 17th World Congress on Medical and Health Informatics. ed. / Brigitte Seroussi; Lucila Ohno-Machado; Lucila Ohno-Machado; Brigitte Seroussi. IOS Press, 2019. p. 1498-1499 (Studies in Health Technology and Informatics; Vol. 264).

研究成果: 書籍/レポートタイプへの寄稿 › 会議への寄与

Izukura, R, Kandabashi, T, Wakata, Y, Nojiri, C, Nohara, Y, Yamashita, T, Takada, A, Park, J, Uyama, Y & Nakashima, N 2019, The development of an electronic phenotyping algorithm for identifying rhabdomyolysis patients in the Mid-NEt database. in B Seroussi, L Ohno-Machado, L Ohno-Machado & B Seroussi (eds), MEDINFO 2019: Health and Wellbeing e-Networks for All - Proceedings of the 17th World Congress on Medical and Health Informatics. Studies in Health Technology and Informatics, vol. 264, IOS Press, pp. 1498-1499, 17th World Congress on Medical and Health Informatics, MEDINFO 2019, Lyon, フランス, 8/25/19. https://doi.org/10.3233/SHTI190503

Izukura R, Kandabashi T, Wakata Y, Nojiri C, Nohara Y, Yamashita T その他. The development of an electronic phenotyping algorithm for identifying rhabdomyolysis patients in the Mid-NEt database. In Seroussi B, Ohno-Machado L, Ohno-Machado L, Seroussi B, editors, MEDINFO 2019: Health and Wellbeing e-Networks for All - Proceedings of the 17th World Congress on Medical and Health Informatics. IOS Press. 2019. p. 1498-1499. (Studies in Health Technology and Informatics). doi: 10.3233/SHTI190503

Izukura, Rieko ; Kandabashi, Tadashi ; Wakata, Yoshifumi その他. / The development of an electronic phenotyping algorithm for identifying rhabdomyolysis patients in the Mid-NEt database. MEDINFO 2019: Health and Wellbeing e-Networks for All - Proceedings of the 17th World Congress on Medical and Health Informatics. editor / Brigitte Seroussi ; Lucila Ohno-Machado ; Lucila Ohno-Machado ; Brigitte Seroussi. IOS Press, 2019. pp. 1498-1499 (Studies in Health Technology and Informatics).

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abstract = "We aimed to develop rhabdomyolysis (RB) phenotyping algorithms using machine learning techniques and to create subphenotyping algorithms to identify RB patients who lack RB diagnosis. Two pattern algorithms, one with a focus on improving predictive value and one focused on improving sensitivity, were finally created and had a high area under the curve value of 0.846. Although we were unable to create subphenotyping algorithms, an attempt to detect unknown RB patients is important for epidemiological studies.",

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The development of an electronic phenotyping algorithm for identifying rhabdomyolysis patients in the Mid-NEt database

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出版物シリーズ

会議

!!!All Science Journal Classification (ASJC) codes

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