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Identification of Pathological Formations in the Lungs Based on Machine Learning Methods
Shakhmametova, G.R., Vakkazov, N.O., Zulkarneev, R.KH. (2020)
The article discusses the use of deep neural networks for analysis and recognition of images
Reliability analysis of power distribution network based on Pso-DBN
Shan, H., Sun, Y., Zhang, W., Kudreyko, A., Ren, L. (2020)
the superiority of applying deep neural network to the reliability analysis of distribution network. © 2020
NEURAL NETWORK MODEL AS THE MULTIDISCIPLINARY TEAM MEMBER IN CLINICAL DECISION SUPPORT TO AVOID MEDICAL MISTAKES (ALYNX CONCEPT)
Buzaev, Igor V., Plechev, Vladimir V., Nikolaeva, Irina E., Galimova, Rezida (2017)
algorithm, for example, a neural network model in decision-making system to avoid possible mistakes in a
Multilayer Convolutional Neural Network Computer Vision Is Effective in Automatic OCT Image Processing
Mustafina, IA, Ishmetov, V., Zagidullin, N, Buzaev, IV (2022)
Multilayer Convolutional Neural Network Computer Vision Is Effective in Automatic OCT Image
ВОЗМОЖНОСТИ ЭКСПЕРТНЫХ СИСТЕМ В ПРОГНОЗИРОВАНИИ ОПЕРАЦИОННОГО РИСКА ПРИ НАИБОЛЕЕ РАСПРОСТРАНЕННЫХ ВМЕШАТЕЛЬСТВАХ В АБДОМИНАЛЬНОЙ ХИРУРГИИ
CAPABILITIES OF EXPERT SYSTEMS IN FORECASTING OPERATIONAL RISK FOR THE MOST COMMON INTERVENTIONS OF ABDOMINAL SURGERY
БОГДАНОВА, Ю.А., ЗАРИПОВА, Г.Р., КАТАЕВ, В.А., ГАЛИМОВ, О.В., Bogdanova, Y.A., Zaripova, G.R., Kataev, V.A., Galimov, O.V. (2016)
ARTIFICIAL NEURAL NETWORKS
Construction of lncRNA-associated ceRNA networks to identify prognostic lncRNA biomarkers for glioblastoma
LIU, Z., WANG, X., YANG, G., ZHONG, C., ZHANG, R., YE, J., ZHONG, Y., HU, J., OZAL, B., ZHAO, S. (2020)
RNA-related ceRNA regulatory network, in glioblastoma (GBM) has not been fully elucidated. The goal
Joint decision-making of parallel machine scheduling restricted in job-machine release time and preventive maintenance with remaining useful life constraints
He, X., Wang, Z., Li, Y., Khazhina, S., Du, W., Wang, J., Wang, W. (2022)
accurate than three common methods (Encoder-Decoder Recurrent Neural Network, Bidirectional Long Short
Construction of a TF–miRNA–gene feed-forward loop network predicts biomarkers and potential drugs for myasthenia gravis
Bo, C., Zhang, H., Cao, Y., Lu, X., Zhang, C., Li, S., Kong, X., Zhang, X., Bai, M., Tian, K., Saitgareeva, A., Lyaysan, G., Wang, J., Ning, S., Wang, L. (2021)
of transcription factors (TFs) and the relationship among them remain unclear. A TF–miRNA–gene network (TMGN) of MG
IDENTIFICATION OF HUB GENES AND SMALL-MOLECULE COMPOUNDS RELATED TO INTRACEREBRAL HEMORRHAGE WITH BIOINFORMATICS ANALYSIS
LIU, Z., ZHANG, R., CHEN, X., YAO, P., YAN, T., LIU, W., YAO, J., ZHAO, S., SOKHATSKII, A., GAREEV, I. (2019)
through PPI network analysis were verified in the rat model of ICH. In addition, we obtained three small
Human-Induced Pluripotent Stem Cells-Derived Corneal Endothelial-Like Cells Promote Corneal Transparency in a Rabbit Model of Bullous Keratopathy
Sun, BQ, Bikkuzin, T, Li, XR, Shi, Y, Zhang, H (2021)
neural crest

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