| A framework for Bayesian optimization in embedded subspaces A Nayebi, A Munteanu, M Poloczek International Conference on Machine Learning, 4752-4761, 2019 | 130 | 2019 |
| A self-supervised learning-based approach to clustering multivariate time-series data with missing values (SLAC-Time): An application to TBI phenotyping H Ghaderi, B Foreman, A Nayebi, S Tipirneni, CK Reddy, V Subbian Journal of Biomedical Informatics 143, 104401, 2023 | 7 | 2023 |
| Recurrent Neural Network based Time-Series Modeling for Long-term Prognosis Following Acute Traumatic Brain Injury A Nayebi, S Tipirneni, B Foreman, J Ratcliff, CK Reddy, V Subbian Proceedings of the American Medical Informatics Association Annual Symposium, 2021 | 7 | 2021 |
| WindowSHAP: An efficient framework for explaining time-series classifiers based on Shapley values A Nayebi, S Tipirneni, CK Reddy, B Foreman, V Subbian Journal of Biomedical Informatics 144, 104438, 2023 | 4 | 2023 |
| Identifying TBI Physiological States by Clustering of Multivariate Clinical Time-Series H Ghaderi, B Foreman, A Nayebi, S Tipirneni, CK Reddy, V Subbian arXiv e-prints, arXiv: 2303.13024, 2023 | 3* | 2023 |
| Predicting Failure of Noninvasive Respiratory Support Using Deep Recurrent Learning JM Mosier, A Nayebi, JM Fisher, V Subbian Respiratory Care 68 (4), 488-496, 2023 | 2 | 2023 |
| An empirical comparison of explainable artificial intelligence methods for clinical data: a case study on traumatic brain injury A Nayebi, S Tipirneni, B Foreman, CK Reddy, V Subbian AMIA annual symposium proceedings 2022, 815, 2022 | 2 | 2022 |
Vignesh SubbianAssociate Professor, University of ArizonaAdresă de e-mail confirmată pe arizona.edu
