Amirhessam Tahmassebi

17 papers B 4Journal 3Unranked 10
YearRankTypeTitle / Venue / Authors
2024 J jnl
Controllability of Functional and Structural Brain Networks.
Complex.
Ali Moradi Amani, Amirhessam Tahmassebi, Andreas Stadlbauer, Uwe Meyer-Baese, Vincent Noblet, Frederic Blanc, Hagen Malberg, Anke Meyer-Baese
2022 J jnl
Evolutionary Machine Learning: A Survey.
ACM Comput. Surv.
Akbar Telikani, Amirhessam Tahmassebi, Wolfgang Banzhaf, Amir H. Gandomi
2022 — conf
Graph signal processing to identify biomarkers in brain networks in dementia.
Biomedical Applications in Molecular, Structural, and Functional Imaging
Amirhessam Tahmassebi, Kevin Mueller, Uwe Meyer-Baese, Jorge Munilla, Andrés Ortiz, Anke Meyer-Baese
2021 B conf
An Evolutionary Framework for Real-Time Fraudulent Credit Detection.
CEC
Behshad Mohebali, Gelareh Karbaschi, Amirhessam Tahmassebi, Anke Meyer-Baese, Amir H. Gandomi
2021 — conf
Identifying the diffusion source of dementia spreading in structural brain networks.
Biomedical Applications in Molecular, Structural, and Functional Imaging
Luke Van Popering, Amirhessam Tahmassebi, Uwe Meyer-Baese, Martin Dyrba, Jorge Munilla, Andrés Ortiz, Anke Meyer-Baese
2021 — conf
Structural Target Controllability of Brain Networks in Dementia.
EMBC
Amirhessam Tahmassebi, Uwe Meyer-Baese, Anke Meyer-Baese
2020 — conf
An Interpretable Deep Learning Framework for Health Monitoring Systems: A Case Study of Eye State Detection using EEG Signals.
SSCI
Amirhessam Tahmassebi, Jennifer Martin, Anke Meyer-Baese, Amir H. Gandomi
2020 — conf
Controllability of structural brain networks in dementia.
Biomedical Applications in Molecular, Structural, and Functional Imaging
Lisa Meyer-Bäse, Fatima Saad, Amirhessam Tahmassebi
2018 B conf
A Pareto Front Based Evolutionary Model for Airfoil Self-Noise Prediction.
CEC
Amirhessam Tahmassebi, Amir H. Gandomi, Anke Meyer-Baese
2018 B conf
An Evolutionary Online Framework for MOOC Performance Using EEG Data.
CEC
Amirhessam Tahmassebi, Amir H. Gandomi, Anke Meyer-Baese
2018 — conf
Deep Learning in Medical Imaging: fMRI Big Data Analysis via Convolutional Neural Networks.
PEARC
Amirhessam Tahmassebi, Amir H. Gandomi, Ian McCann, Mieke H. J. Schulte, Anna E. Goudriaan, Anke Meyer-Baese
2018 — conf
Determining disease evolution driver nodes in dementia networks.
Biomedical Applications in Molecular, Structural, and Functional Imaging
Amirhessam Tahmassebi, Ali Moradi Amani, Katja Pinker-Domenig, Anke Meyer-Baese
2018 — conf
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
Amirhessam Tahmassebi, Katja Pinker-Domenig, Georg Wengert, Thomas H. Helbich, Zsuzsanna Bago-Horvath, Anke Meyer-Baese
2018 J jnl
Optimized Naive-Bayes and Decision Tree Approaches for fMRI Smoking Cessation Classification.
Complex.
Amirhessam Tahmassebi, Amir H. Gandomi, Mieke H. J. Schulte, Anna E. Goudriaan, Simon Y. Foo, Anke Meyer-Baese
2017 B conf
An evolutionary approach for fMRI big data classification.
CEC
Amirhessam Tahmassebi, Amir H. Gandomi, Ian McCann, Mieke H. J. Schulte, Lianne Schmaal, Anna E. Goudriaan, Anke Meyer-Baese
2017 — conf
Genetic Programming Based on Error Decomposition: A Big Data Approach.
GPTP
Amirhessam Tahmassebi, Amir H. Gandomi
2017 — conf
High Performance GP-Based Approach for fMRI Big Data Classification.
PEARC
Amirhessam Tahmassebi, Amir H. Gandomi, Anke Meyer-Bäse