Knowledge Graph Enhanced Transformers for Diagnosis Generation of Chinese Medicine

Chinese medicine(CM)diagnosis intellectualization is one of the hotspots in the research of CM modernization.The traditional CM intelligent diagnosis models transform the CM diagnosis issues into classification issues,however,it is difficult to solve the problems such as excessive or similar categories.With the development of natural language processing techniques,text generation technique has become increasingly mature.In this study,we aimed to establish the CM diagnosis generation model by transforming the CM diagnosis issues into text generation issues.The semantic context characteristic learning capacity was enhanced referring to Bidirectional Long Short-Term Memory(BILSTM)with Transformer as the backbone network.Meanwhile,the CM diagnosis generation model Knowledge Graph Enhanced Transformer(KGET)was established by introducing the knowledge in medical field to enhance the inferential capability.The KGET model was established based on 566 CM case texts,and was compared with the classic text generation models including Long Short-Term Memory sequence-to-sequence(LSTM-seq2seq),Bidirectional and Auto-Regression Transformer(BART),and Chinese Pre-trained Unbalanced Transformer(CPT),so as to analyze the model manifestations.Finally,the ablation experiments were performed to explore the influence of the optimized part on the KGET model.The results of Bilingual Evaluation Understudy(BLEU),Recall-Oriented Understudy for Gisting Evaluation 1(ROUGE1),ROUGE2 and Edit distance of KGET model were 45.85,73.93,54.59 and 7.12,respectively in this study.Compared with LSTM-seq2seq,BART and CPT models,the KGET model was higher in BLEU,ROUGE1 and ROUGE2 by 6.00–17.09,1.65–9.39 and 0.51–17.62,respectively,and lower in Edit distance by 0.47–3.21.The ablation experiment results revealed that introduction of BILSTM model and prior knowledge could significantly increase the model performance.Additionally,the manual assessment indicated that the CM diagnosis results of the KGET model used in this study were highly consistent with the practical diagnosis results.In conclusion,text generation technology can be effectively applied to CM diagnostic modeling.It can effectively avoid the problem of poor diagnostic performance caused by excessive and similar categories in traditional CM diagnostic classification models.CM diagnostic text generation technology has broad application prospects in the future.

Can New Diagnostic Criteria of Rheumatoid Arthritis Really Make An Early Diagnosis？ --A Case Report of Early Diagnosis and Treatment of Early Rheumatoid Arthritis with Chinese Medicine

Introduction Rheumatoid arthritis （RA） is a chronic systemic disease in which immunologically mediated inflammation of synovia-lined joints can result in marked disruption of joint structure and function. With advances in our understanding of the pathogenesis of RA over the past two decades,

Systems response profiles to two Rehmanniae Radix formulae in metabolic syndrome patients

Objective: To explore the effects of two Rehmanniae Radix formulae in patients with metabolic syndrome(Met S), a randomized controlled study was conducted.Methods: Met S patients were randomly assigned to receive either a classic Rehmanniae Six Formula(R6, or ‘Liu Wei Di Huang Wan') or a novel multi-herbal Rehmanniae Radix containing formula SUB889 for 8 weeks. Western medicine related clinical parameters, Chinese medicine defined symptoms and syndromes as well as metabolomic profiles were evaluated at different time points.Results: R6(n = 20) and SUB889(n = 20) showed similar effects on Met S regarding the improvement of clinical parameters(waist circumference, body mass index, LDL-cholesterol, systolic blood pressure) and Qi/Yin deficiency(p < 0.05). Decreased levels of cholesteryl esters, phosphatidylcholines, triglycerides and sphingomyelins were found in the R6 group, while SUB889 formula resulted in increased levels of tricarboxylic acid cycle and glucose metabolism intermediates(malate, fumarate and pyruvate).Conclusions: R6 and SUB889 have similar effects on the treatment of Met S by improving Chinese medicine and Western medicine defined clinical outcomes. R6 is more effective in improving lipid profiles compared to SUB889. The exact mechanisms of the two formulae on Met S remain to be elucidated.