基于TF-IDF量化的模糊诊断矩阵在中医诊断中的应用

Application of Fuzzy Diagnostic Matrix Based on TF-IDF Quantization in TCM Diagnosis

以TF-IDF相对熵为证候的量化依据,构建症状-证型模糊诊断矩阵,并以此为基础,结合患者的症状矢量空间,建立中医证候诊断的推理模型及推理机制。实验表明,此模型对中医证候诊断是可行的,也为中医智能化诊断中的机器学习,提供了一种重要的途径与方法。

Based on the relative entropy of TF-IDF,this paper constructs the symptom-syndrome fuzzy diagnosis matrix.Based on this,combined with the symptom vector space of the patients,the reasoning model and reasoning mechanism of TCM syndrome diagnosis are established. Experiments show that this model is feasible for the diagnosis of TCM syndromes,and also provides an important way and method for machine learning in intelligent diagnosis of Chinese medicine.