TCM Medical Record Analysis Algorithm Based on Recurrent Convolutional Neural Network

Abstract

The most important step in the process of medical record analysis in TCM is the classification of medical records. The biggest challenge of medical record classification is to perceive the correlation between context words and find keywords, and make judgments based on the keyword information. In this article, we propose a TCM medical record analysis algorithm based on recurrent convolutional neural network, which introduces a maximum pooling layer in the recurrent neural network, and uses it to determine the words that play an important role in text classification to capture the key components of the text. Experimental results show that recurrent convolutional neural network achieves better results than attention recurrent neural network and traditional recurrent neural network. In addition, recurrent convolutional neural network is more than twice as fast as them in terms of training speed.