Identification and assessment of risk factors associated with diseases are necessary to increase the effectiveness of preventive measures. This problem is particularly important for such a socially significant disease as stroke. The use of automated methods for analyzing large arrays of electronic health records can increase the efficiency of extracting information about risk factors. This work presents one of these methods, that is based on using the constructed rules and a linguistic parser.
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Blagosklonov N. A., Donitova V. V., Kireev D. A., Kobrinskii B. A., Smirnov I. V. Linguistic analysis of electronic health records for extraction of stroke risk factors // Proceeding of the Institute for Systems Analysis of the Russian Academy of Science. 2020. Vol. 70. № 3. pp. 75-85.