Abstract
AbstractThis paper proposes a method of construction of discharge summaries classifier. First, morphological and correspondence analysis generates a term matrix from text data. Then, machine learning methods are applied to a term matrix. The method compared several machine learning methods by using discharge summaries stored in hospital information system. The experimental results show that random forest is the best clasifier, compared with deep learning, SVM and decision tree.
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