BERT and Word Segmentation Algorithm Research on the Relationship Between Diabetes Symptoms and Traditional Chinese Medicine

Diabetes is a common chronic Metabolic disorder, and its treatment has always been a hot research topic in the medical field. Traditional Chinese medicine has a significant therapeutic effect on it and has become one of the important ways for patients to choose treatment methods. In recent years, with the development and application of deep learning technology, more and more research has begun to attempt to use deep learning models to process traditional Chinese medicine case data, achieving automated information extraction and analysis. This study shows that BERT model and jieba segmentation algorithm have good effect in the study of the relationship between symptoms and Medication in diabetes medical record data, which is expected to provide scientific basis and reference for clinical treatment of traditional Chinese medicine.