| Enhancing IoT anomaly detection performance for federated learning B Weinger, J Kim, A Sim, M Nakashima, N Moustafa, KJ Wu Digital Communications and Networks 8 (3), 314-323, 2022 | 51 | 2022 |
| Anomaly detection based on traffic monitoring for secure blockchain networking J Kim, M Nakashima, W Fan, S Wuthier, X Zhou, I Kim, SY Chang 2021 IEEE International Conference on Blockchain and Cryptocurrency (ICBC), 1-9, 2021 | 30 | 2021 |
| Automated feature selection for anomaly detection in network traffic data M Nakashima, A Sim, Y Kim, J Kim, J Kim ACM Transactions on Management Information Systems (TMIS) 12 (3), 1-28, 2021 | 17 | 2021 |
| A machine learning approach to anomaly detection based on traffic monitoring for secure blockchain networking J Kim, M Nakashima, W Fan, S Wuthier, X Zhou, I Kim, SY Chang IEEE Transactions on Network and Service Management 19 (3), 3619-3632, 2022 | 13 | 2022 |
| Evaluation of deep learning models for network performance prediction for scientific facilities M Nakashima, A Sim, J Kim Proceedings of the 3rd International Workshop on Systems and Network …, 2020 | 7 | 2020 |
| Lightweight and identifier-oblivious engine for cryptocurrency networking anomaly detection W Fan, HJ Hong, J Kim, S Wuthier, M Nakashima, X Zhou, CH Chow, ... IEEE Transactions on Dependable and Secure Computing 20 (2), 1302-1318, 2022 | 6 | 2022 |
| Deep learning analysis using cardiovascular magnetic resonance imaging for risk prediction in cardiac amyloidosis J Cockrum, D Chen, M Nakashima, J Mauch, MA Hanna, K Kanj, ... Journal of the American College of Cardiology 79 (9_Supplement), 1193-1193, 2022 | 1 | 2022 |
| A Machine Learning Approach to Peer Connectivity Estimation for Reliable Blockchain Networking J Kim, M Nakashima, W Fan, S Wuthier, X Zhou, I Kim, SY Chang 2021 IEEE 46th Conference on Local Computer Networks (LCN), 319-322, 2021 | 1 | 2021 |
| FEASIBILITY OF ESTIMATION OF PULMONARY CAPILLARY WEDGE PRESSURE BY MRI IN CARDIAC AMYLOIDOSIS J Simkowski, D Salam, M Nakashima, D Chen, LG Tereshchenko, ... Journal of the American College of Cardiology 83 (13_Supplement), 1544-1544, 2024 | | 2024 |
| LGE SEGMENTATION PROVIDES INCREMENTAL PROGNOSTIC RISK STRATIFICATION IN PATIENTS WITH CARDIAC AMYLOIDOSIS J Simkowski, D Salam, M Nakashima, D Chen, A Firth, WHW Tang, ... Journal of the American College of Cardiology 83 (13_Supplement), 1542-1542, 2024 | | 2024 |
| Reducing Contextual Bias in Cardiac Magnetic Resonance Imaging Deep Learning Using Contrastive Self-Supervision M Nakashima, D Salem, HWW Tang, C Nguyen, TH Hwang, D Zhao, ... Machine Learning for Healthcare Conference, 473-488, 2023 | | 2023 |
| Multimodal Representation Learning of Cardiovascular Magnetic Resonance Imaging J Qiu, P Huang, M Nakashima, J Lee, J Zhu, W Tang, P Chen, C Nguyen, ... arXiv preprint arXiv:2304.07675, 2023 | | 2023 |
| QUANTITATIVE LATE GADOLINIUM ENHANCEMENT IN CARDIOVASCULAR MAGNETIC RESONANCE IMAGING AS A PREDICTOR OF MORTALITY IN PATIENTS WITH CARDIAC AMYLOIDOSIS D Salam, J Cockrum, Y Salam, J Simkowski, D Chen, M Nakashima, ... Journal of the American College of Cardiology 81 (8_Supplement), 1523-1523, 2023 | | 2023 |
| MYOCARDIAL DEFORMATION ASSESSMENT PROVIDES SUPERIOR INCREMENTAL PROGNOSTIC RISK STRATIFICATION IN PATIENTS WITH CARDIAC AMYLOIDOSIS COMPARED TO LATE GADOLINIUM ENHANCEMENT J Simkowski, D Salam, Y Salam, J Cockrum, K Wolski, Q Wang, D Chen, ... Journal of the American College of Cardiology 81 (8_Supplement), 1522-1522, 2023 | | 2023 |
| Segmentation Improves Deep Learning Accuracy for Differentiating Non-Ischemic and Ischemic Cardiomyopathy Using Cardiac Mri Cine Imaging M Nakashima, J Cockrum, D Salam, S Mazumder, K Sreedhara, ... NaN, NaN-NaN, 2023 | | 2023 |
| Interaction of a priori Anatomic Knowledge with Self-Supervised Contrastive Learning in Cardiac Magnetic Resonance Imaging M Nakashima, I Jang, R Basnet, M Benovoy, WH Tang, C Nguyen, ... arXiv preprint arXiv:2205.12429, 2022 | | 2022 |
| Comparison of Deep Learning and Radiomic Features to Differentiate Non-Ischemic and Ischemic Cardiomyopathy Using Cardiac MRI Cine Imaging M Nakashima, D Chen, R Basnet, M Benovoy, TH Hwang, R Geschke, ... Circulation 144 (Suppl_1), A12691-A12691, 2021 | | 2021 |
| Prioritizing Variables for Network Traffic Analysis M Nakashima Texas A&M University-Commerce, 2020 | | 2020 |
| An Ensemble Approach toward Automated Variable Selection for Network Anomaly Detection M Nakashima, A Sim, Y Kim, J Kim, J Kim arXiv preprint arXiv:1910.12806, 2019 | | 2019 |
| Digital Communications and Networks B Weinger, J Kim, A Sim, M Nakashima, N Moustafa, KJ Wu | | |
