Performance evaluation and extraction of significant factors from medical text

Abstract

The digitalization of medical treatment has progressed and huge amounts of medical data are accumulating. Electronic medical data include structured numerical data and unstructured text data. The medical text analysis is expected to improve medical process and the clinical decision support. The present paper analyzes the words that appear in operation records to predict the two peaks and the long hospitalization by Support vector machine, and evaluated them by Feature selection. Three measures were proposed and the prediction performance for importance of the feature word was evaluated. Two measures obtained that less than 10 words resulted in the optimal prediction performance. Moreover, it was confirmed the effect of medical dictionary.