Multistage analysis method for detection of effective herb prescription from clinical data / 医学前沿

Determining effective traditional Chinese medicine (TCM) treatments for specific disease conditions or particular patient groups is a difficult issue that necessitates investigation because of the complicated personalized manifestations in real-world patients and the individualized combination therapies prescribed in clinical settings. In this study, a multistage analysis method that integrates propensity case matching, complex network analysis, and herb set enrichment analysis was proposed to identify effective herb prescriptions for particular diseases (e.g., insomnia). First, propensity case matching was applied to match clinical cases. Then, core network extraction and herb set enrichment were combined to detect core effective herb prescriptions. Effectiveness-based mutual information was used to detect strong herb-symptom relationships. This method was applied on a TCM clinical data set with 955 patients collected from well-designed observational studies. Results revealed that groups of herb prescriptions with higher effectiveness rates (76.9% vs. 42.8% for matched samples; 94.2% vs. 84.9% for all samples) compared with the original prescriptions were found. Particular patient groups with symptom manifestations were also identified to help investigate the indications of the effective herb prescriptions.

Research Review of Knowledge Graph and Its Application in TCM Field / 中国中医药信息杂志

As the new development of scientometrics and informetrics, knowledge graph has infiltrated into the financial, industrial and medical fields, and become a hot issue in the real world research. In this article, the concept and features of knowledge graph, construction and the existing softwares, the application status and development prospect in the TCM field were reviewed, which may provide references for research on the knowledge graph in the TCM field.