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System of diagnosis of acute nazhopharingitis using artificial neural networks

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dc.contributor.author Hussein A.
dc.contributor.author Salman M.
dc.contributor.author Burnashev R.
dc.date.accessioned 2020-01-15T22:12:03Z
dc.date.available 2020-01-15T22:12:03Z
dc.date.issued 2019
dc.identifier.uri https://dspace.kpfu.ru/xmlui/handle/net/157013
dc.description.abstract © 2019 IEEE. - This paper deals with the task of analyzing data for medical personnel and patients, namely, providing medical care to children and adults with acute respiratory viral infection (acute nasopharyngitis). Using the Python environment and supporting libraries for working with data in the PostgreSQL database management system, medical data analysis was performed. Subsequently, the patients were diagnosed. This process was carried out using medical card of clinical recommendations for providing medical care to children and adults with such disease. Methods of mathematical theory (mathematical statistics and regression analysis) were adopted and applied in specialized software as an experiment on one hand, while data analysis methods and algorithms were carried out in a free software on the other hand. To perform these tasks, a program was developed using the Python environment and the TensorFlow library. The analysis of the experimental studies results was carried out. The basic patterns of influence of patient diagnosis indicators on diagnosis, data structure parameters, graphical diagrams using the matplotlib library were identified, and the result was positive. (Abstract)
dc.subject Data analysis
dc.subject Medical record
dc.subject Neural network
dc.subject PostgreSQL
dc.subject Python
dc.title System of diagnosis of acute nazhopharingitis using artificial neural networks
dc.type Conference Paper
dc.collection Публикации сотрудников КФУ
dc.relation.startpage 344
dc.source.id SCOPUS-2019-SID85075899674


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  • Публикации сотрудников КФУ Scopus [24551]
    Коллекция содержит публикации сотрудников Казанского федерального (до 2010 года Казанского государственного) университета, проиндексированные в БД Scopus, начиная с 1970г.

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