Latent class model based diagnostic system utilizing traditional Chinese medicine for patients with systemic lupus erythematosus

Abstract

Systemic lupus erythematosus (SLE) can affect nearly any organ system, and is frequently an evolving disease with varied manifestations. Traditional Chinese medicine (TCM) physicians have identified different SLE patterns that they have difficulty summarizing, but the latent class model helps solve this problem. This study applies the latent class model and disease pattern coding system (B-code) to design a TCM diagnostic expert system. This study gathered 2047 valid records and classified three clusters of main disease patterns. Compared with the experience of the TCM expert, the accuracy rate of the expert system reached 77.47%. The results show that this diagnostic system performed well in identifying the disease patterns of SLE and may be clinically useful for TCM physicians.