Abstract
This article describes the study results in the development of the method of analysis of semi-structured data from electronic health records to improve the quality of data describing patients’ treatment processes. Improving the accuracy of information retrieval from electronic medical records was achieved by using developed problem-solving oriented library. Moreover, the latent-semantic analysis of the electronic health records of chronic patients with chronic heart failure, diabetes mellitus, hypertension was performed. The main tokens characterizing different groups of patients were revealed. The developed library and semantic analysis based on it can be used to accurately automatic extraction of information from semi-structured electronic medical records. Automated markup of medical texts on the Russian language is also possible for the development of artificial intelligence systems and new generation clinical decision support systems.
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