Paweł Pławiak
Cited by
Cited by
Arrhythmia detection using deep convolutional neural network with long duration ECG signals
Ö Yıldırım, P Pławiak, RS Tan, UR Acharya
Elsevier Computers in Biology and Medicine 102 (11), 411-420, 2018
Novel Methodology of Cardiac Health Recognition Based on ECG Signals and Evolutionary-Neural System
P Pławiak
Elsevier Expert Systems with Applications 92 (2018), 334-349, 2018
Novel Deep Genetic Ensemble of Classifiers for Arrhythmia Detection Using ECG Signals
P Pławiak, UR Acharya
Springer Neural Computing and Applications 32 (2020), 11137–11161, 2020
Novel Genetic Ensembles of Classifiers Applied to Myocardium Dysfunction Recognition Based on ECG Signals
P Pławiak
Elsevier Swarm and Evolutionary Computation 39 (2018), 192-208, 2018
A New Machine Learning Technique for an Accurate Diagnosis of Coronary Artery Disease
M Abdar, W Książek, UR Acharya, RS Tan, V Makarenkov, P Pławiak
Elsevier Computer Methods and Programs in Biomedicine 179 (2019), 104992, 2019
Hand Body Language Gesture Recognition Based on Signals From Specialized Glove and Machine Learning Algorithms
P Plawiak, T Sosnicki, M Niedzwiecki, Z Tabor, K Rzecki
IEEE Transactions on Industrial Informatics 12 (3), 1104 - 1113, 2016
Automated arrhythmia detection using novel hexadecimal local pattern and multilevel wavelet transform with ECG signals
T Tuncer, S Dogan, P Pławiak, UR Acharya
Elsevier Knowledge-Based Systems 186 (2019), 104923, 2019
Application of new deep genetic cascade ensemble of SVM classifiers to predict the Australian credit scoring
P Pławiak, M Abdar, UR Acharya
Elsevier Applied Soft Computing 84 (2019), 105740, 2019
A Novel Machine Learning Approach for Early Detection of Hepatocellular Carcinoma Patients
W Książek, M Abdar, UR Acharya, P Pławiak
Elsevier Cognitive Systems Research 54 (2019), 116-127, 2019
DGHNL: A New Deep Genetic Hierarchical Network of Learners for Prediction of Credit Scoring
P Pławiak, M Abdar, J Pławiak, V Makarenkov, UR Acharya
Elsevier Information Sciences 516 (2020), 401-418, 2020
Approximation of phenol concentration using novel hybrid computational intelligence methods
P Pławiak, R Tadeusiewicz
International Journal of Applied Mathematics and Computer Science 24 (1 …, 2014
ResNet‐Attention model for human authentication using ECG signals
M Hammad, P Pławiak, K Wang, UR Acharya
Wiley Expert Systems, e12547, 2020
Person Recognition based on Touch Screen Gestures using Computational Intelligence Methods
K Rzecki, P Pławiak, M Niedźwiecki, T Sośnicki, J Leśkow, M Ciesielski
Elsevier Information Sciences 415 (2017), 70-84, 2017
Classification of tea specimens using novel hybrid artificial intelligence methods
P Pławiak, W Maziarz
Elsevier Sensors and Actuators B: Chemical 192 (2014), 117-125, 2014
Towards Real-Time Heartbeat Classification: Evaluation of Nonlinear Morphological Features and Voting Method
RNVPS Kandala, R Dhuli, P Pławiak, G Naik, H Moeinzadeh, ...
MDPI Sensors 19 (23), 5079, 2019
Approximation of Phenol Concentration using Computational Intelligence Methods Based on Signals from the Metal Oxide Sensor Array
P Plawiak, K Rzecki
IEEE Sensors Journal 15 (3), 1770 - 1783, 2015
IAPSO-AIRS: A Novel Improved Machine Learning-based System for Wart Disease Treatment
M Abdar, VN Wijayaningrum, S Hussain, R Alizadehsani, P Pławiak, ...
Springer Journal of Medical Systems 43 (2019), 220, 2019
An estimation of the state of consumption of a positive displacement pump based on dynamic pressure or vibrations using neural networks
P Pławiak
Elsevier Neurocomputing 144 (2014), 471-483, 2014
Application of Computational Intelligence Methods for the Automated Identification of Paper-Ink Samples Based on LIBS
K Rzecki, T Sośnicki, M Baran, M Niedźwiecki, M Król, T Łojewski, ...
MDPI Sensors 18 (11), 3670, 2018
Hybrid particle swarm optimization for rule discovery in the diagnosis of coronary artery disease
M Zomorodi‐moghadam, M Abdar, Z Davarzani, X Zhou, P Pławiak, ...
Wiley Expert Systems 38 (1), 1-17, 2021
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