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 |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| dx.doi.org-10.1088-1742-6596-881-1-012009.pdf | 552,93 kB | Adobe PDF | View/Open |
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