Аleksandr V. Gusev, Roman E. Novitskiy, Aleksandr A. Ivshin, Juliia S. Boldina, Аleksey S. Shtykov, Аleksey S. Vasilev
Abstract:
Development of artificial intelligence methods in medicine requires large volumes of input data available. The source of this data is electronic health records. Extraction of data from health records is accompanied by a number of difficulties, mainly associated with their being filled out in any form and doctors using various abbreviations when putting down the information. The paper describes a method of processing electronic health records which allows extracting the necessary information from them – the one needed for building work algorithms of artificial intelligence software complexes and their learning. The method was developed and tested out on electronic health records filled out in Russian. For working with medical documents filled out in other languages, it needs no special adaptation. For this, it is sufficient to change teaching data and perform complete learning of all models
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Aleksandr V. Gusev, Roman E. Novitskiy, Aleksandr A. Ivshin, Juliia S. Boldina, Aleksey S. Shtykov, Aleksey S. Vasilev. Extraction of medical data from electronic medical records using NLP algorithms. Ad Alta, Journal of Interdisciplinary Research, 2022, volume 12, issue 02, P.314-319, http://www.doi.org/10.33543/1202
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