The evaluation of functional heart condition with machine learning algorithms
Электронный архив ТПУ
Информация об архиве | Просмотр оригинала| Поле | Значение | |
| Заглавие |
The evaluation of functional heart condition with machine learning algorithms
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| Автор |
Overchuk, K. V.
Lezhnina, Inna Alekseevna Uvarov, Aleksandr Andreevich Perchatkin, V. A. Lvova, A. B. |
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| Тематика |
функциональное состояние
сердце алгоритмы машинное обучение классификаторы |
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| Описание |
This paper is considering the most suitable algorithms to build a classifier for evaluating of the functional heart condition with the ability to estimate the direction and progress of the patient's treatment. The cons and pros of algorithms was analyzed with respect to the problem posed. The most optimal solution has been given and justified.
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| Дата |
2017-11-08T09:07:40Z
2017-11-08T09:07:40Z 2017 |
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| Тип |
Conference Paper
Published version (info:eu-repo/semantics/publishedVersion) Conference paper (info:eu-repo/semantics/conferencePaper) |
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| Идентификатор |
The evaluation of functional heart condition with machine learning algorithms / K. V. Overchuk [et al.] // Journal of Physics: Conference Series. — 2017. — Vol. 881 : Innovations in Non-Destructive Testing (SibTest 2017) : International Conference, 27–30 June 2017, Novosibirsk, Russian Federation : [proceedings]. — [012009, 5 p.].
http://earchive.tpu.ru/handle/11683/43878 10.1088/1742-6596/881/1/012009 |
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| Язык |
en
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| Связанные ресурсы |
Journal of Physics: Conference Series. Vol. 881 : Innovations in Non-Destructive Testing (SibTest 2017). — Bristol, 2017.
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| Права |
Open access (info:eu-repo/semantics/openAccess)
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| Издатель |
IOP Publishing
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