205 citations
- Institute of Physics and TechnologyKZ15 papers
- Center for Astrophysics Harvard & SmithsonianUS4 papers
- Damghan UniversityIR4 papers
- Joint Institute for Nuclear ResearchRU4 papers
- Search for Extraterrestrial IntelligenceUS4 papers
- University of OxfordGB4 papers
- Bellevue Hospital CenterUS3 papers
- Erzincan Binali Yıldırım UniversityTR3 papers
- Evgeni Kharadze Georgian National Astrophysical ObservatoryGE3 papers
- Fesenkov Astrophysical InstituteKZ3 papers
- Goddard Space Flight CenterUS3 papers
- Indian Statistical InstituteIN3 papers
11 papers · 1 filter
A Bio-Inspired Chaos Sensor Model Based on the Perceptron Neural Network: Machine Learning Concept and Application for Computational Neuro-Science
Andrei Velichko, Petr Boriskov, Maksim Belyaev +1
The study presents a bio-inspired chaos sensor model based on the perceptron neural network for the estimation of entropy of spike train in neurodynamic systems. After training, th…
Neural Network Entropy (NNetEn): Entropy-Based EEG Signal and Chaotic Time Series Classification, Python Package for NNetEn Calculation
Andrei Velichko, Maksim Belyaev, Yuriy Izotov +2
Entropy measures are effective features for time series classification problems. Traditional entropy measures, such as Shannon entropy, use probability distribution function. Howev…
Detection of Risk Predictors of COVID-19 Mortality with Classifier Machine Learning Models Operated with Routine Laboratory Biomarkers
Mehmet Tahir Huyut, Andrei Velichko, Maksim Belyaev
Early evaluation of patients who require special care and who have high death-expectancy in COVID-19, and the effective determination of relevant biomarkers on large sample-groups…
Entropy Approximation by Machine Learning Regression: Application for Irregularity Evaluation of Images in Remote Sensing
Andrei Velichko, Maksim Belyaev, Matthias P. Wagner +1
Approximation of entropies of various types using machine learning (ML) regression methods are shown for the first time. The ML models presented in this study define the complexity…
Machine Learning Sensors for Diagnosis of COVID-19 Disease Using Routine Blood Values for Internet of Things Application
Andrei Velichko, Mehmet Tahir Huyut, Maksim Belyaev +2
Healthcare digitalization requires effective applications of human sensors, when various parameters of the human body are instantly monitored in everyday life due to the Internet o…
Diagnosis and Prognosis of COVID-19 Disease Using Routine Blood Values and LogNNet Neural Network
Mehmet Tahir Huyut, Andrei Velichko
Since February 2020, the world has been engaged in an intense struggle with the COVID-19 dis-ease, and health systems have come under tragic pressure as the disease turned into a p…