Please use this identifier to cite or link to this item: http://earchive.tpu.ru/handle/11683/43878
Title: The evaluation of functional heart condition with machine learning algorithms
Authors: Overchuk, K. V.
Lezhnina, Inna Alekseevna
Uvarov, Aleksandr Andreevich
Perchatkin, V. A.
Lvova, A. B.
Keywords: функциональное состояние; сердце; алгоритмы; машинное обучение; классификаторы
Issue Date: 2017
Publisher: IOP Publishing
Citation: 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.].
Abstract: 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.
URI: http://earchive.tpu.ru/handle/11683/43878
Appears in Collections:Материалы конференций

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