A Semantic Analysis and Community Detection-Based Artificial Intelligence Model for Core Herb Discovery from the Literature: Taking Chronic Glomerulonephritis Treatment as a Case Study

<div>The framework of CHDSC. CHDSC consists of two modules, semantic analysis and community detection, in which the former is a Chinese word embedding algorithm ESSP2VEC to analyse the semantics of herbs and the latter is a label propagation-based algorithm LILPA to detect herb communities and core herbs. As a case study, we take CGN as an example and discover core herbs to treat different syndromes of CGN.</div>

Computational and Mathematical Methods in Medicine

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Figure 1: A Semantic Analysis and Community Detection-Based Artificial Intelligence Model for Core Herb Discovery from the Literature: Taking Chronic Glomerulonephritis Treatment as a Case Study 

Figure 1 | A Semantic Analysis and Community Detection-Based Artificial Intelligence Model for Core Herb Discovery from the Literature: Taking Chronic Glomerulonephritis Treatment as a Case Study 