Development of a neural network for diagnosing the risk of depression according to the experimental data of the stop signal paradigm
- DOI
- 10.18699/vjgb-22-93
- Published
- 2023-01-04
- Container
- Vavilov Journal of Genetics and Breeding
- Publisher
- Institute of Cytology and Genetics, SB RAS
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.18699/vjgb-22-93,
title = {Development of a neural network for diagnosing the risk of depression according to the experimental data of the stop signal paradigm},
author = {M. O. Zelenskih and A. E. Saprygin and S. S. Tamozhnikov and P. D. Rudych and D. A. Lebedkin and A. N. Savostyanov},
year = {2023},
journal = {Vavilov Journal of Genetics and Breeding},
doi = {10.18699/vjgb-22-93},
url = {https://doi.org/10.18699/vjgb-22-93}
}RIS
TY - JOUR TI - Development of a neural network for diagnosing the risk of depression according to the experimental data of the stop signal paradigm AU - M. O. Zelenskih AU - A. E. Saprygin AU - S. S. Tamozhnikov AU - P. D. Rudych AU - D. A. Lebedkin AU - A. N. Savostyanov PY - 2023 JO - Vavilov Journal of Genetics and Breeding DO - 10.18699/vjgb-22-93 UR - https://doi.org/10.18699/vjgb-22-93 ER -
APA
Zelenskih, M. O., Saprygin, A. E., Tamozhnikov, S. S., Rudych, P. D., Lebedkin, D. A., & Savostyanov, A. N. (2023). Development of a neural network for diagnosing the risk of depression according to the experimental data of the stop signal paradigm. Vavilov Journal of Genetics and Breeding. https://doi.org/10.18699/vjgb-22-93
Source records
- crossref · retrieved 2026-09-25T00:01:08.303Z