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Amirhessam Tahmassebi
Amirhessam Tahmassebi
PhD in Computational Science, Department of Scientific Computing, Florida State University
Verified email at FSU.edu - Homepage
Title
Cited by
Cited by
Year
Impact of machine learning with multiparametric magnetic resonance imaging of the breast for early prediction of response to neoadjuvant chemotherapy and survival outcomes in …
A Tahmassebi, GJ Wengert, TH Helbich, Z Bago-Horvath, S Alaei, ...
Investigative radiology 54 (2), 110-117, 2019
2382019
Evolutionary machine learning: A survey
A Telikani, A Tahmassebi, W Banzhaf, AH Gandomi
ACM Computing Surveys (CSUR) 54 (8), 1-35, 2021
1652021
Probabilistic neural networks: a brief overview of theory, implementation, and application
B Mohebali, A Tahmassebi, A Meyer-Baese, AH Gandomi
Handbook of probabilistic models, 347-367, 2020
1212020
Deep learning in medical imaging: fmri big data analysis via convolutional neural networks
A Tahmassebi, AH Gandomi, I McCann, MHJ Schulte, AE Goudriaan, ...
Proceedings of the practice and experience on advanced research computing, 1-4, 2018
562018
Building energy consumption forecast using multi-objective genetic programming
A Tahmassebi, AH Gandomi
Measurement 118, 164-171, 2018
552018
AI‐Enhanced Diagnosis of Challenging Lesions in Breast MRI: A Methodology and Application Primer
A Meyer‐Base, L Morra, A Tahmassebi, M Lobbes, U Meyer‐Base, ...
Journal of magnetic resonance imaging 54 (3), 686-702, 2021
372021
Multi-stage optimization of a deep model: A case study on ground motion modeling
A Tahmassebi, AH Gandomi, S Fong, A Meyer-Baese, SY Foo
PloS one 13 (9), e0203829, 2018
322018
Optimized naive‐Bayes and decision tree approaches for fMRI smoking cessation classification
A Tahmassebi, AH Gandomi, MHJ Schulte, AE Goudriaan, SY Foo, ...
Complexity 2018 (1), 2740817, 2018
292018
ideeple: Deep learning in a flash
A Tahmassebi
Disruptive Technologies in Information Sciences 10652, 177-193, 2018
262018
XGBoost model as an efficient machine learning approach for PFAS removal: Effects of material characteristics and operation conditions
E Karbassiyazdi, F Fattahi, N Yousefi, A Tahmassebi, AA Taromi, ...
Environmental Research 215, 114286, 2022
252022
An evolutionary approach for fmri big data classification
A Tahmassebi, AH Gandomi, I McCann, MHJ Schulte, L Schmaal, ...
2017 IEEE Congress on Evolutionary Computation (CEC), 1029-1036, 2017
232017
An evolutionary online framework for MOOC performance using EEG data
A Tahmassebi, AH Gandomi, A Meyer-Baese
2018 IEEE Congress on Evolutionary Computation (CEC), 1-8, 2018
222018
Using machine learning to identify karst sinkholes from LiDAR-derived topographic depressions in the Bluegrass Region of Kentucky
J Zhu, AM Nolte, N Jacobs, M Ye
Journal of Hydrology 588, 125049, 2020
212020
Handbook of probabilistic models
P Samui, DT Bui, S Chakraborty, R Deo
Butterworth-Heinemann, 2019
182019
Genetic programming based on error decomposition: A big data approach
A Tahmassebi, AH Gandomi
Genetic programming theory and practice XV, 135-147, 2018
182018
Determining disease evolution driver nodes in dementia networks
A Tahmassebi, AM Amani, K Pinker-Domenig, A Meyer-Baese
Medical Imaging 2018: Biomedical Applications in Molecular, Structural, and …, 2018
172018
A big data inspired preprocessing scheme for bandwidth use optimization in smart cities applications using raspberry pi
B Mohebali, A Tahmassebi, AH Gandomi, A Meyer-Baese
Big Data: Learning, Analytics, and Applications 10989, 1098902, 2019
152019
Genetic Programming Theory and Practice XVI
W Banzhaf, L Spector, L Sheneman
Springer International Publishing, 2019
152019
Big data analytics in medical imaging using deep learning
A Tahmassebi, A Ehtemami, B Mohebali, AH Gandomi, K Pinker, ...
Big Data: Learning, Analytics, and Applications 10989, 86-101, 2019
142019
High performance gp-based approach for fmri big data classification
A Tahmassebi, AH Gandomi, A Meyer-Bäse
Proceedings of the Practice and Experience in Advanced Research Computing …, 2017
142017
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Articles 1–20