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vitaly schetinin
vitaly schetinin
Senior Lecturer in Machine Learnig, University of Bedfordshire
Verified email at beds.ac.uk - Homepage
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Cited by
Cited by
Year
Confident interpretation of Bayesian decision tree ensembles for clinical applications
V Schetinin, JE Fieldsend, D Partridge, TJ Coats, WJ Krzanowski, ...
IEEE Transactions on Information Technology in Biomedicine 11 (3), 312-319, 2007
902007
Review of machine learning approach on credit card fraud detection
R Bin Sulaiman, V Schetinin, P Sant
Human-Centric Intelligent Systems 2 (1), 55-68, 2022
772022
A learning algorithm for evolving cascade neural networks
V Schetinin
Neural Processing Letters 17, 21-31, 2003
702003
Bayesian averaging over decision tree models for trauma severity scoring
V Schetinin, L Jakaite, W Krzanowski
Artificial Intelligence in Medicine 84, 139-145, 2018
482018
Feature extraction with GMDH-type neural networks for EEG-based person identification
V Schetinin, L Jakaite, N Nyah, D Novakovic, W Krzanowski
International Journal of Neural Systems 28 (06), 1750064, 2018
412018
Deep learning for early detection of pathological changes in x-ray bone microstructures: case of osteoarthritis
L Jakaite, V Schetinin, J Hladůvka, S Minaev, A Ambia, W Krzanowski
Scientific Reports 11 (1), 2294, 2021
382021
Bayesian Assessment of Newborn Brain Maturity from Two‐Channel Sleep Electroencephalograms
L Jakaite, V Schetinin, C Maple
Computational and Mathematical Methods in Medicine 2012 (1), 629654, 2012
382012
Feature extraction from electroencephalograms for Bayesian assessment of newborn brain maturity
L Jakaite, V Schetinin, J Schult
2011 24th International Symposium on Computer-Based Medical Systems (CBMS), 1-6, 2011
382011
Filament recognition in solar images with the neural network technique
VV Zharkova, V Schetinin
Solar Physics 228, 137-148, 2005
372005
Bayesian decision trees for EEG assessment of newborn brain maturity
L Jakaite, V Schetinin, C Maple, J Schult
2010 UK Workshop on Computational Intelligence (UKCI), 1-6, 2010
362010
The combined technique for detection of artifacts in clinical electroencephalograms of sleeping newborns
V Schetinin, J Schult
IEEE Transactions on Information Technology in Biomedicine 8 (1), 28-35, 2004
352004
Extraction of features from sleep EEG for Bayesian assessment of brain development
V Schetinin, L Jakaite
PloS one 12 (3), e0174027, 2017
322017
Bayesian averaging over decision tree models: an application for estimating uncertainty in trauma severity scoring
V Schetinin, L Jakaite, W Krzanowski
International journal of medical informatics 112, 6-14, 2018
312018
Classification of newborn EEG maturity with Bayesian averaging over decision trees
V Schetinin, L Jakaite
Expert Systems with Applications 39 (10), 9340-9347, 2012
312012
Polynomial neural networks learnt to classify EEG signals
V Schetinin
arXiv preprint cs/0504058, 2005
312005
Bayesian learning of models for estimating uncertainty in alert systems: application to air traffic conflict avoidance
V Schetinin, L Jakaite, W Krzanowski
Integrated Computer-Aided Engineering 25 (3), 229-245, 2018
302018
Evolving polynomial neural networks for detecting abnormal patterns
N Nyah, L Jakaite, V Schetinin, P Sant, A Aggoun
2016 IEEE 8th international conference on intelligent systems (IS), 74-80, 2016
282016
Prediction of survival probabilities with Bayesian decision trees
V Schetinin, L Jakaite, WJ Krzanowski
Expert Systems with Applications 40 (14), 5466-5476, 2013
282013
Bayesian decision trees for predicting survival of patients: A study on the US national trauma data bank
V Schetinin, L Jakaite, J Jakaitis, W Krzanowski
Computer Methods and Programs in Biomedicine 111 (3), 602-612, 2013
262013
Confidence in classification: a bayesian approach
WJ Krzanowski, TC Bailey, D Partridge, JE Fieldsend, RM Everson, ...
Journal of Classification 23, 199-220, 2006
262006
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