Takanori Yamashita, Y. Wakata, S. Hamai, Y. Nakashima, Y. Iwamoto, Brendan Flanagan, N. Nakashima, S. Hirokawa
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Construction of Dominant Factor Presumption Model for Postoperative Hospital Days from Operation Records
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.
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