Construction of dominant factor presumption model for postoperative hospital days from operation records

Takanori Yamashita, Yoshifumi Wakata, Satoshi Hamai, Yasuharu Nakashima, Yukihide Iwamoto, Brendan Flanagan, Naoki Nakashima, Sachio Hirokawa

研究成果: 会議への寄与タイプ学会誌査読

抄録

The secondary use of clinical text data to improve the quality and the efficiency of medical care is gaining much attention. However, there are few previous researches that have given feedback to clinical situations. The present paper analyzes the words that appear in operation records to predict the postoperative length of stay. SVM (support vector machine) and feature selection are applied to predict if a stay is longer than the standard length of 25 days. It was confirmed that with less than 20 feature words we can predict if a stay is longer or not with almost the optimal prediction performance.

本文言語英語
ページ19-24
ページ数6
DOI
出版ステータス出版済み - 9月 29 2014
イベント3rd IIAI International Conference on Advanced Applied Informatics, IIAI-AAI 2014 - Kitakyushu, 日本
継続期間: 8月 31 20149月 4 2014

その他

その他3rd IIAI International Conference on Advanced Applied Informatics, IIAI-AAI 2014
国/地域日本
CityKitakyushu
Period8/31/149/4/14

!!!All Science Journal Classification (ASJC) codes

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