Sequence generation model of traditional Chinese medicine

The application of artificial intelligence in the field of traditional Chinese medicine is more and more extensive, and the related research is also more and more. Increasingly, the electronic processing of TCM textual information is becoming more and more important. In this paper, we propose a TCM text-based prescription generation task, intending to be able to implement automatic prescription generation functions based on the sequence-to-sequence (seq2seq) model. Traditional TCM prescriptions are given by the attending physicians, and the prescription recommendation system proposed in this paper achieves a certain degree of accuracy compared to real doctors. After a series of system data training, we improved the accuracy rate to 76%. For FI the value reached the best result of 74% at the existing stage.