John Thomas
Orcid: 0000-0003-0144-3746Affiliations:
- Rochester Institute of Technology, Department of Electrical and Computer Engineering Technology, Rochester, NY, USA
- McGill University, Montreal Neurological Institut, Montreal, Canada
- Nanyang Technological University (NTU), School of Electrical and Electronic Engineering, Singapore
According to our database1,
John Thomas authored at least 17 papers
between 2016 and 2024.
Collaborative distances:
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Timeline
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Bibliography
2024
Automated Multi-Class Seizure-Type Classification System Using EEG Signals and Machine Learning Algorithms.
IEEE Access, 2024
2023
Six-Center Assessment of CNN-Transformer with Belief Matching Loss for Patient-Independent Seizure Detection in EEG.
Int. J. Neural Syst., March, 2023
Comprehensive Analysis of Feature Extraction Methods for Emotion Recognition from Multichannel EEG Recordings.
Sensors, January, 2023
Low Valence Low Arousal Stimuli: An Effective Candidate for EEG-Based Biometrics Authentication System.
Proceedings of the Caring is Sharing - Exploiting the Value in Data for Health and Innovation - Proceedings of MIE 2023, Gothenburg, Sweden, 22, 2023
Optimization of Pre-Ictal Interval Time Period for Epileptic Seizure Prediction Using Temporal and Frequency Features.
Proceedings of the Caring is Sharing - Exploiting the Value in Data for Health and Innovation - Proceedings of MIE 2023, Gothenburg, Sweden, 22, 2023
Proceedings of the Healthcare Transformation with Informatics and Artificial Intelligence, 2023
2021
Automated Adult Epilepsy Diagnostic Tool Based on Interictal Scalp Electroencephalogram Characteristics: A Six-Center Study.
Int. J. Neural Syst., 2021
Time-Frequency Decomposition of Scalp Electroencephalograms Improves Deep Learning-Based Epilepsy Diagnosis.
Int. J. Neural Syst., 2021
Multi-Center Validation Study of Automated Classification of Pathological Slowing in Adult Scalp Electroencephalograms Via Frequency Features.
Int. J. Neural Syst., 2021
2020
Automated Detection of Interictal Epileptiform Discharges from Scalp Electroencephalograms by Convolutional Neural Networks.
Int. J. Neural Syst., 2020
Deep Learning for Interictal Epileptiform Spike Detection from scalp EEG frequency sub bands.
Proceedings of the 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2020
2018
EEG CLassification Via Convolutional Neural Network-Based Interictal Epileptiform Event Detection.
Proceedings of the 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2018
Proceedings of the 52nd Asilomar Conference on Signals, Systems, and Computers, 2018
2017
Proceedings of the 2017 IEEE International Conference on Systems, Man, and Cybernetics, 2017
Automated epileptiform spike detection via affinity propagation-based template matching.
Proceedings of the 2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2017
2016
Proceedings of the 2016 IEEE International Conference on Acoustics, 2016