Discovery of Traditional Chinese Medicine Prescription Patterns Containing Herbal Dosage Based on Multilevel Top-K Weighted Association Rules

Multiple prescription pattern recognition model based on Siamese network

Prescription data is an important focus and breakthrough in the study of clinical treatment rules, and the complex multidimensional relationships between Traditional Chinese medicine (TCM) prescription data increase the difficulty of extracting knowledge from clinical data. This paper proposes a complex prescription recognition algorithm (MTCMC) based on the classification and matching of TCM prescriptions with classical prescriptions to identify the classical prescriptions contained in the prescriptions and provide a reference for mining TCM knowledge. The MTCMC algorithm first calculates the importance level of each drug in the complex prescriptions and determines the core prescription combinations of patients through the Analytic Hierarchy Process (AHP) combined with drug dosage. Secondly, a drug attribute tagging strategy was used to quantify the functional features of each drug in the core prescriptions; finally, a Bidirectional Long Short-Term Memory Network (BiLSTM) was used to extract the relational features of the core prescriptions, and a vector representation similarity matrix was constructed in combination with the Siamese network framework to calculate the similarity between the core prescriptions and the classical prescriptions. The experimental results show that the accuracy and F1 score of the prescription matching dataset constructed based on this paper reach 94.45% and 94.34% respectively, which is a significant improvement compared with the models of existing methods.

Traditional Chinese medicines and natural products targeting immune cells in the treatment of metabolic-related fatty liver disease

MAFLD stands for metabolic-related fatty liver disease, which is a prevalent liver disease affecting one-third of adults worldwide, and is strongly associated with obesity, hyperlipidemia, and type 2 diabetes. It encompasses a broad spectrum of conditions ranging from simple liver fat accumulation to advanced stages like chronic inflammation, tissue damage, fibrosis, cirrhosis, and even hepatocellular carcinoma. With limited approved drugs for MAFLD, identifying promising drug targets and developing effective treatment strategies is essential. The liver plays a critical role in regulating human immunity, and enriching innate and adaptive immune cells in the liver can significantly improve the pathological state of MAFLD. In the modern era of drug discovery, there is increasing evidence that traditional Chinese medicine prescriptions, natural products and herb components can effectively treat MAFLD. Our study aims to review the current evidence supporting the potential benefits of such treatments, specifically targeting immune cells that are responsible for the pathogenesis of MAFLD. By providing new insights into the development of traditional drugs for the treatment of MAFLD, our findings may pave the way for more effective and targeted therapeutic approaches.