Extracting diagnosis rules using fuzzy binary decision tree for pregnancy consultations

摘要

Aiming at alleviating the load of the maternity hospital, online diagnosis for pregnancy consultations is urgently needed. In this paper, we focus on extracting knowledge from clinical data to guide conversations between humans (pregnant women) and machines (medical knowledge base). To achieve this, a fuzzy binary decision tree model is used. The experimental results show that this model outperforms others and the generated decision tree could successfully guide the process of pregnancy consultations.