Subjects: Library Science,Information Science >> Information Science submitted time 2017-10-11 Cooperative journals: 《数据分析与知识发现》
Abstract: [Objective] This study aims to extract knowledge for clinical decision from electronic medical records through semantic analysis. [Methods] We first extracted clinical terms from the training samples by the word segmentation algorithm with the help of custom dictionary and statistical method. Then, we used latent semantic analysis to find the potential correlations between clinical terms and treatment plans. Finally, we established a latent semantic model to support gastric cancer treatments. [Results] We successfully extracted 605 treatment plans from 1000 test samples based on the discharge summary texts. [Limitations] Only discharge record texts were examined for this study. [Conclusions] The latent semantic analysis could effectively process electronic medical records to assist doctors’ clinical decision-making work, which posed positive effects to the development of electronic medical record applications.