| Prospective, multi-site study of patient outcomes after implementation of the TREWS machine learning-based early warning system for sepsis R Adams, KE Henry, A Sridharan, H Soleimani, A Zhan, N Rawat, ... Nature medicine 28 (7), 1455-1460, 2022 | 86 | 2022 |
| Recursive Gath–Geva clustering as a basis for evolving neuro-fuzzy modeling H Soleimani-B, C Lucas, BN Araabi Evolving Systems 1, 59-71, 2010 | 85 | 2010 |
| Scalable joint models for reliable uncertainty-aware event prediction H Soleimani, J Hensman, S Saria IEEE transactions on pattern analysis and machine intelligence 40 (8), 1948-1963, 2018 | 69 | 2018 |
| Treatment-response models for counterfactual reasoning with continuous-time, continuous-valued interventions H Soleimani, A Subbaswamy, S Saria arXiv preprint arXiv:1704.02038, 2017 | 59 | 2017 |
| Semi-supervised multi-label topic models for document classification and sentence labeling H Soleimani, DJ Miller Proceedings of the 25th ACM international on conference on information and …, 2016 | 48 | 2016 |
| Parsimonious Topic Models with Salient Word Discovery H Soleimani, DJ Miller Knowledge and Data Engineering, IEEE Transactions on 27 (3), 2014 | 44 | 2014 |
| ATD: Anomalous topic discovery in high dimensional discrete data H Soleimani, DJ Miller IEEE Transactions on Knowledge and Data Engineering 28 (9), 2267-2280, 2016 | 40 | 2016 |
| Factors driving provider adoption of the TREWS machine learning-based early warning system and its effects on sepsis treatment timing KE Henry, R Adams, C Parent, H Soleimani, A Sridharan, L Johnson, ... Nature medicine 28 (7), 1447-1454, 2022 | 35 | 2022 |
| An analytical solution for free liquid sloshing in a finite-length horizontal cylindrical container filled to an arbitrary depth SM Hasheminejad, H Soleimani Applied Mathematical Modelling 48, 338-352, 2017 | 21 | 2017 |
| Adaptive prediction of epileptic seizures from intracranial recordings H Soleimani-B, C Lucas, B N Araabi, L Schwabe Biomedical Signal Processing and Control 7 (5), 456-464, 2012 | 20 | 2012 |
| Semisupervised, multilabel, multi-instance learning for structured data H Soleimani, DJ Miller Neural computation 29 (4), 1053-1102, 2017 | 12 | 2017 |
| Exploiting the value of class labels on high-dimensional feature spaces: topic models for semi-supervised document classification H Soleimani, DJ Miller Pattern Analysis and Applications 22, 299-309, 2019 | 8 | 2019 |
| Fast evolving neuro-fuzzy model and its application in online classification and time series prediction H Soleimani-B, C Lucas, BN Araabi Pattern Analysis & Applications 15 (3), 279-288, 2012 | 8 | 2012 |
| Automating measurement of trainee work hours H Soleimani, J Adler‐Milstein, RJ Cucina, SG Murray Journal of Hospital Medicine 16 (7), 404-408, 2021 | 7 | 2021 |
| Characterizing styles of clinical note production and relationship to clinical work hours among first-year residents JJ Gong, H Soleimani, SG Murray, J Adler-Milstein Journal of the American Medical Informatics Association 29 (1), 120-127, 2022 | 6 | 2022 |
| Sparse topic models by parameter sharing H Soleimani, DJ Miller 2014 IEEE International Workshop on Machine Learning for Signal Processing …, 2014 | 4 | 2014 |
| Estimation of surgical resident duty hours and workload in real time using electronic health record data JA Lin, L Pierce, SG Murray, H Soleimani, EC Wick, JA Sosa, K Hirose Journal of surgical education 78 (6), e232-e238, 2021 | 3 | 2021 |
| Early Identification Of Gastrointestinal Bleeding Requiring Critical Care Using Machine Learning H Soleimani, K Henry, A Zhan, P Pronovost, N Rawat, D Hager, S Saria Am J Respir Crit Care Med 195, A7145, 2017 | 3 | 2017 |
| Exploiting the value of class labels in topic models for semi-supervised document classification H Soleimani, DJ Miller 2016 International Joint Conference on Neural Networks (IJCNN), 4025-4031, 2016 | 3 | 2016 |
| On an Objective Basis for the Maximum Entropy Principle DJ Miller, H Soleimani Entropy 17 (1), 401-406, 2015 | 3 | 2015 |
Dr. Suchi SariaJohn C. Malone Endowed Chair; Computer Science, Statistics, Medicine, Health Policy, Johns HopkinsDirección de correo verificada de cs.jhu.edu
