DC Field | Value | Language |
dc.contributor.author | Nishanov, A. K. | - |
dc.contributor.author | Jurayev, G. P. | - |
dc.contributor.author | Narziyev, N. B. | - |
dc.date.accessioned | 2020-06-03T11:35:32Z | - |
dc.date.available | 2020-06-03T11:35:32Z | - |
dc.date.issued | 2020 | - |
dc.identifier.citation | Nishanov, А. K. Adaptable genetic algorithm for primary processing of medical data based on random search / А. K. Nishanov, G. P. Jurayev, N. B. Narziyev // BIG DATA and Advanced Analytics = BIG DATA и анализ высокого уровня: сб. материалов VI Междунар. науч.-практ. конф., Минск, 20-21 мая 2020 года: в 3 ч. Ч. 1 / редкол. : В. А. Богуш [и др.]. – Минск : Бестпринт, 2020. – С. 147–155. | ru_RU |
dc.identifier.isbn | 978-985-90533-7-5 | - |
dc.identifier.uri | https://libeldoc.bsuir.by/handle/123456789/39027 | - |
dc.description.abstract | In the article the topical software tool "Algorithmic and computer software for the primary processing of medical data" has been developed, and based on it several practical issues related to cardiology have been solved in visualized way. The software is based on methods and algorithms for solving such issues as preprocessing of data generated by medical professionals, re-classifying study facilities and determining the importance of classes, creating table charts, and selecting a set of informative symbols that differentiate between class objects. | ru_RU |
dc.language.iso | en | ru_RU |
dc.publisher | Беспринт | ru_RU |
dc.subject | материалы конференций | ru_RU |
dc.subject | Fishers criterion | ru_RU |
dc.subject | feature selection | ru_RU |
dc.subject | algorithms for an estimate calculation | ru_RU |
dc.subject | preprocessing of medical data | ru_RU |
dc.subject | algorithm "A" | ru_RU |
dc.subject | flexible genetic algorithm | ru_RU |
dc.title | Adaptable genetic algorithm for primary processing of medical data based on random search | ru_RU |
dc.type | Статья | ru_RU |
Appears in Collections: | BIG DATA and Advanced Analytics = BIG DATA и анализ высокого уровня : материалы конференции (2020)
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