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Proceedings Paper

Docking as a way to analyze biomedical data
Author(s): M. V. Postnova; G. A. Sroslova; A. V. Kovalenko; Y. A. Zimina
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Paper Abstract

The paper demonstrates the importance of neural networks, which are successfully used in various fields. Artificial neural networks demonstrate a large number of brain properties. They are trained on the basis of experience, generalize previous precedents to new cases and extract significant properties from incoming information which contains excessive data. Technically, training is to find coefficients of connections between neurons. In the process of learning, a neural network is able to detect complex dependencies between input and output data, and also perform generalization. As a result, the analysis showed that, on average, the neural network made 50% of forecasts.

Paper Details

Date Published: 3 June 2019
PDF: 6 pages
Proc. SPIE 11067, Saratov Fall Meeting 2018: Computations and Data Analysis: from Nanoscale Tools to Brain Functions, 110670M (3 June 2019); doi: 10.1117/12.2523104
Show Author Affiliations
M. V. Postnova, Volgograd State Univ. (Russian Federation)
G. A. Sroslova, Volgograd State Univ. (Russian Federation)
A. V. Kovalenko, Volgograd State Univ. (Russian Federation)
Y. A. Zimina , Volgograd State Univ. (Russian Federation)


Published in SPIE Proceedings Vol. 11067:
Saratov Fall Meeting 2018: Computations and Data Analysis: from Nanoscale Tools to Brain Functions
Dmitry Engelevich Postnov, Editor(s)

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