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Amirhessam Tahmassebi
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2020 – today
- 2024
- [j3]Ali Moradi Amani
, Amirhessam Tahmassebi
Controllability of Functional and Structural Brain Networks. Complex. 2024 (2024) - 2022
- [j2]Akbar Telikani, Amirhessam Tahmassebi, Wolfgang Banzhaf, Amir H. Gandomi
Evolutionary Machine Learning: A Survey. ACM Comput. Surv. 54(8): 161:1-161:35 (2022) - [c14]Amirhessam Tahmassebi, Kevin Mueller, Uwe Meyer-Baese, Jorge Munilla, Andrés Ortiz
Graph signal processing to identify biomarkers in brain networks in dementia. Biomedical Applications in Molecular, Structural, and Functional Imaging 2022 - 2021
- [c13]Behshad Mohebali, Gelareh Karbaschi, Amirhessam Tahmassebi, Anke Meyer-Baese, Amir H. Gandomi
An Evolutionary Framework for Real-Time Fraudulent Credit Detection. CEC 2021: 1999-2006 - [c12]Amirhessam Tahmassebi, Uwe Meyer-Baese, Anke Meyer-Baese:
Structural Target Controllability of Brain Networks in Dementia. EMBC 2021: 3978-3981 - [c11]Luke Van Popering, Amirhessam Tahmassebi, Uwe Meyer-Baese, Martin Dyrba
Identifying the diffusion source of dementia spreading in structural brain networks. Biomedical Applications in Molecular, Structural, and Functional Imaging 2021 - 2020
- [c10]Lisa Meyer-Bäse, Fatima Saad
Controllability of structural brain networks in dementia. Biomedical Applications in Molecular, Structural, and Functional Imaging 2020: 113171W - [c9]Amirhessam Tahmassebi, Jennifer Martin, Anke Meyer-Baese, Amir H. Gandomi
An Interpretable Deep Learning Framework for Health Monitoring Systems: A Case Study of Eye State Detection using EEG Signals. SSCI 2020: 211-218
2010 – 2019
- 2018
- [j1]Amirhessam Tahmassebi
Optimized Naive-Bayes and Decision Tree Approaches for fMRI Smoking Cessation Classification. Complex. 2018: 2740817:1-2740817:24 (2018) - [c8]Amirhessam Tahmassebi, Amir H. Gandomi
An Evolutionary Online Framework for MOOC Performance Using EEG Data. CEC 2018: 1-8 - [c7]Amirhessam Tahmassebi, Amir H. Gandomi
A Pareto Front Based Evolutionary Model for Airfoil Self-Noise Prediction. CEC 2018: 1-8 - [c6]Amirhessam Tahmassebi
Determining the importance of parameters extracted from multi-parametric MRI in the early prediction of the response to neo-adjuvant chemotherapy in breast cancer. Biomedical Applications in Molecular, Structural, and Functional Imaging 2018: 1057818 - [c5]Amirhessam Tahmassebi
Determining disease evolution driver nodes in dementia networks. Biomedical Applications in Molecular, Structural, and Functional Imaging 2018: 1057829 - [c4]Amirhessam Tahmassebi, Amir H. Gandomi
Deep Learning in Medical Imaging: fMRI Big Data Analysis via Convolutional Neural Networks. PEARC 2018: 85:1-85:4 - 2017
- [c3]Amirhessam Tahmassebi, Amir H. Gandomi, Ian McCann, Mieke H. J. Schulte, Lianne Schmaal, Anna E. Goudriaan, Anke Meyer-Baese:
An evolutionary approach for fMRI big data classification. CEC 2017: 1029-1036 - [c2]Amirhessam Tahmassebi, Amir H. Gandomi
Genetic Programming Based on Error Decomposition: A Big Data Approach. GPTP 2017: 135-147 - [c1]Amirhessam Tahmassebi, Amir H. Gandomi, Anke Meyer-Bäse:
High Performance GP-Based Approach for fMRI Big Data Classification. PEARC 2017: 57:1-57:4
Coauthor Index
aka: Anke Meyer-Baese
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last updated on 2024-11-28 21:28 CET by the dblp team
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