| Evaluating a widely implemented proprietary deterioration index model among hospitalized patients with COVID-19 K Singh, TS Valley, S Tang, BY Li, F Kamran, MW Sjoding, J Wiens, ... Annals of the American Thoracic Society 18 (7), 1129-1137, 2021 | 95* | 2021 |
| Democratizing EHR analyses with FIDDLE: a flexible data-driven preprocessing pipeline for structured clinical data S Tang, P Davarmanesh, Y Song, D Koutra, MW Sjoding, J Wiens Journal of the American Medical Informatics Association 27 (12), 1921-1934, 2020 | 71 | 2020 |
| Model selection for offline reinforcement learning: Practical considerations for healthcare settings S Tang, J Wiens Machine Learning for Healthcare Conference, 2-35, 2021 | 62 | 2021 |
| Early identification of patients admitted to hospital for covid-19 at risk of clinical deterioration: model development and multisite external validation study S Tang, F Kamran, E Otles, DS McEvoy, SN Saleh, J Gong, BY Li, S Dutta, ... BMJ 2022 (376), e068576, 2022 | 39 | 2022 |
| Predicting acute graft-versus-host disease using machine learning and longitudinal vital sign data from electronic health records S Tang, GT Chappell, A Mazzoli, M Tewari, SW Choi, J Wiens JCO clinical cancer informatics 4, 128-135, 2020 | 36 | 2020 |
| Clinician-in-the-loop decision making: Reinforcement learning with near-optimal set-valued policies S Tang, A Modi, M Sjoding, J Wiens International Conference on Machine Learning, 9387-9396, 2020 | 22 | 2020 |
| Leveraging Factored Action Spaces for Efficient Offline Reinforcement Learning in Healthcare S Tang, M Makar, M Sjoding, F Doshi-Velez, J Wiens Advances in Neural Information Processing Systems, 2022 | 18 | 2022 |
| Respecting Autonomy And Enabling Diversity: The Effect Of Eligibility And Enrollment On Research Data Demographics S Tang, K Spector-Bagdady, S Jabbour, WN Price, A Bracic, MS Creary, ... Health Affairs 40 (12), 1892-1899, 2021 | 18 | 2021 |
| Relaxed parameter sharing: effectively modeling time-varying relationships in clinical time-series J Oh, J Wang, S Tang, MW Sjoding, J Wiens Machine Learning for Healthcare Conference, 27-52, 2019 | 17* | 2019 |
| Predicting postoperative opioid use with machine learning and insurance claims in opioid-naïve patients S Tang, J Hur, V Gunaseelan, J Vu, CM Brummett, M Englesbe, J Waljee, ... The American Journal of Surgery, 2021 | 10 | 2021 |
| MIMIC-III and eICU-CRD: Feature Representation by FIDDLE Preprocessing S Tang, P Davarmanesh, Y Song, D Koutra, MW Sjoding, J Wiens PhysioNet, 2021 | 2 | 2021 |
| Machine learning for health (ML4H) 2022 A Parziale, M Agrawal, S Tang, K Severson, L Oala, A Subbaswamy, ... Machine Learning for Health, 1-11, 2022 | 1 | 2022 |
| Analysis of Complete Blood Count Data and Use in Classification Machine Learning Models to Predict Icans Incidence Following CAR-T Cell Therapy M Olesnavich, E Sandford, A Ly, A Canbaz, M Rozwadowski, ... Transplantation and Cellular Therapy, Official Publication of the American …, 2024 | | 2024 |
| Machine Learning for Health (ML4H) 2023 S Hegselmann, A Parziale, D Shanmugam, S Tang, K Severson, ... Machine Learning for Health (ML4H), 1-12, 2023 | | 2023 |
| Machine Learning for Health symposium 2023--Findings track S Hegselmann, A Parziale, D Shanmugam, S Tang, MN Asiedu, S Chang, ... arXiv preprint arXiv:2312.00655, 2023 | | 2023 |
| Leveraging Factored Action Spaces for Off-Policy Evaluation A Rebello, S Tang, J Wiens, S Parbhoo arXiv preprint arXiv:2307.07014, 2023 | | 2023 |
| Proceedings of the 3rd Machine Learning for Health Symposium S Hegselmann, A Parziale, D Shanmugam, S Tang, MN Asiedu, S Chang, ... PROCEEDINGS OF MACHINE LEARNING RESEARCH 225, 1-676, 2023 | | 2023 |
| Counterfactual-Augmented Importance Sampling for Semi-Offline Policy Evaluation S Tang, J Wiens Advances in Neural Information Processing Systems 36, 2023 | | 2023 |
| Machine Learning for Health symposium 2022 -- Extended Abstract track A Parziale, M Agrawal, S Joshi, IY Chen, S Tang, L Oala, A Subbaswamy arXiv preprint arXiv:2211.15564, 2022 | | 2022 |
| Towards Data-Driven Offline Simulations for Online Reinforcement Learning S Tang, FV Frujeri, D Misra, A Lamb, J Langford, P Mineiro, S Kochman 3rd Offline Reinforcement Learning Workshop at NeurIPS 2022, 2022 | | 2022 |
Jenna WiensUniversity of MichiganVerified email at umich.edu
