| A weighted support vector machine method for control chart pattern recognition P Xanthopoulos, T Razzaghi Computers & Industrial Engineering 70, 134-149, 2014 | 137 | 2014 |
| A cost-sensitive convolution neural network learning for control chart pattern recognition D Fuqua, T Razzaghi Expert Systems with Applications 150, 113275, 2020 | 99 | 2020 |
| Multilevel weighted support vector machine for classification on healthcare data with missing values T Razzaghi, O Roderick, I Safro, N Marko PloS one 11 (5), e0155119, 2016 | 96 | 2016 |
| Exploring approaches for predictive cancer patient digital twins: Opportunities for collaboration and innovation EA Stahlberg, M Abdel-Rahman, B Aguilar, A Asadpoure, RA Beckman, ... Frontiers in digital health 4, 1007784, 2022 | 56 | 2022 |
| Predictive models for bariatric surgery risks with imbalanced medical datasets T Razzaghi, I Safro, J Ewing, E Sadrfaridpour, J Scott Annals of Operations Research, 2019 | 53 | 2019 |
| Engineering fast multilevel support vector machines E Sadrfaridpour, T Razzaghi, I Safro Machine Learning, arXiv preprint arXiv:1707.07657, 2019 | 38 | 2019 |
| Weighted relaxed support vector machines O Şeref, T Razzaghi, P Xanthopoulos Annals of Operations Research 249, 235-271, 2017 | 24 | 2017 |
| Fast imbalanced classification of healthcare data with missing values T Razzaghi, O Roderick, I Safro, N Marko 2015 18th International Conference on Information Fusion (Fusion), 774-781, 2015 | 23 | 2015 |
| Scalable multilevel support vector machines T Razzaghi, I Safro Procedia Computer Science 51, 2683-2687, 2015 | 23 | 2015 |
| A machine learning and clustering-based approach for county-level COVID-19 analysis C Nicholson, L Beattie, M Beattie, T Razzaghi, S Chen Plos one 17 (4), e0267558, 2022 | 20 | 2022 |
| Relaxed support vector regression OP Panagopoulos, P Xanthopoulos, T Razzaghi, O Şeref Annals of Operations Research 276, 191-210, 2019 | 20 | 2019 |
| An imbalance-aware deep neural network for early prediction of preeclampsia R Bennett, ZD Mulla, P Parikh, A Hauspurg, T Razzaghi Plos one 17 (4), e0266042, 2022 | 19 | 2022 |
| Algebraic multigrid support vector machines I Sadrfaridpour, Ehsan and Jeereddy, Sandeep and Kennedy, Ken and Luckow ... ESANN, European Symposium on Artificial Neural Networks, Computational …, 2017 | 19* | 2017 |
| Constraint relaxation, cost-sensitive learning and bagging for imbalanced classification problems with outliers T Razzaghi, P Xanthopoulos, O Şeref Optimization Letters 11, 915-928, 2017 | 11 | 2017 |
| Personalized Colorectal Cancer Survivability Prediction with Machine Learning Methods* S Li, T Razzaghi 2018 IEEE International Conference on Big Data (Big Data), 2554-2558, 2018 | 5 | 2018 |
| Cost-sensitive learning-based methods for imbalanced classification problems with applications T Razzaghi | 4 | 2014 |
| An imbalance-aware BiLSTM for control chart patterns early detection M Derakhshi, T Razzaghi Expert Systems with Applications 249, 123682, 2024 | 3 | 2024 |
| Machine learning approaches to modeling interdependent network restoration time G Ramineni, N Ghorbani-Renani, K Barker, AD González, T Razzaghi, ... Environment Systems and Decisions 43 (1), 22-35, 2023 | 3 | 2023 |
| Engineering multilevel support vector machines E Sadrfaridpour, T Razzaghi, I Safro arXiv preprint arXiv:1707.07657, 2017 | 3 | 2017 |
| Fast multilevel support vector machines T Razzaghi, I Safro arXiv preprint arXiv:1410.3348, 2014 | 2 | 2014 |
Ilya SafroAssociate Professor of Computer Science, University of Delaware確認したメール アドレス: udel.edu