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Modelling and Data Analysis
2020. Vol. 10, no. 2, 49–61
doi:10.17759/mda.2020100204
ISSN: 2219-3758 / 2311-9454 (online)

The Use of Neural Network Approaches in the Diagnosis of Diseases

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S.K. Akhmed, S.V. Skorodumov

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Abstract

The work is aimed at demonstrating the possibility of using neural network approaches to diagnosing diseases using the example of the diagnosis of coronavirus. A study of the trend in the spread of coronavirus is being conducted, based on data provided by WHO. Conclusions are drawn about the possibility of applying these approaches.

General Information

Keywords: neural networks, multilayer networks, convolutional neural networks, error matrix, WHO, coronavirus

Journal rubric: Artificial Intelligence

Article type: scientific article

DOI: https://doi.org/10.17759/mda.2020100204

For citation: Akhmed, S.K., Skorodumov, S.V. (2020). The Use of Neural Network Approaches in the Diagnosis of Diseases. Modelling and Data Analysis, 10(2), 49–61. (In Russ.). https://doi.org/10.17759/mda.2020100204

References

  1. Andrés Ortiz, Jorge Munilla, Manuel Martínez-Ibañez, Juan M. Górriz, Javier Ramírez and Diego Salas-Gonzalez. Parkinson’s Disease Detection Using Isosurfaces-Based Features and Convolutional Neural Networks. Front Neuroinform. 2019;13:48. doi: 10.3389/fninf.2019.00048
  2. IBM Watson Website [Electronic resource]. IBM Watson. URL: https://www.ibm.com/watson-health
  3. Github [Electronic resource]. Github. https://github.com/Untronix0nly/Articles
  4. Nikolenko S., Kadurin A., Archangelskaya E. Deep learning / / Saint Petersburg: Piter, 2019–480 s: Il.
  5. Imagenet [Electronic resource]. Imagenet competition. URL: http://www.image-net.org/
  6. Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun. Deep Residual Learning for Image Recognition [Electronic resource]. ArXiv. URL: https://arxiv.org/pdf/1512.03385.pdf
  7. Fuzhen Zhuang, Zhiyuan Qi, Keyu Duan, Dongbo Xi, Yongchun Zhu, Hengshu Zhu, Hui Xiong, Qing He. A Comprehensive Survey on Transfer Learning [Electronic resource]. ArXiv. URL: https://arxiv.org/pdf/1911.02685.pdf

Information About the Authors

Samir K. Akhmed, PhD student, Moscow Aviation Institute (National Research University), Moscow, Russian Federation, ORCID: https://orcid.org/0000-0001-5057-4510, e-mail: untronix@outlook.com

Stanislav V. Skorodumov, Associate Professor, Chair 806, Moscow Aviation Institute (National Research University), Moscow, Russian Federation, ORCID: https://orcid.org/0000-0002-0442-2206, e-mail: skorodum@gmail.com

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