| Measuring the impact of AI in the diagnosis of hospitalized patients: a randomized clinical vignette survey study S Jabbour, D Fouhey, S Shepard, TS Valley, EA Kazerooni, N Banovic, ... Jama 330 (23), 2275-2284, 2023 | 174 | 2023 |
| Deep Learning Applied to Chest X-Rays: Exploiting and Preventing Shortcuts S Jabbour, D Fouhey, E Kazerooni, M Sjoding, J Wiens Machine Learning for Healthcare, 2020 | 64 | 2020 |
| Combining chest X-rays and electronic health record (EHR) data using machine learning to diagnose acute respiratory failure S Jabbour, D Fouhey, E Kazerooni, J Wiens, MW Sjoding Journal of the American Medical Informatics Association 29 (6), 1060-1068, 2022 | 35 | 2022 |
| Respecting Autonomy And Enabling Diversity: The Effect Of Eligibility And Enrollment On Research Data Demographics S Jabbour, K Spector-Bagdady, S Tang, WN Price, A Bracic, MS Creary, ... Health Affairs 40 (12), 1892-1899, 2021 | 30 | 2021 |
| Learning concept credible models for mitigating shortcuts J Wang, S Jabbour, M Makar, M Sjoding, J Wiens Advances in neural information processing systems 35, 33343-33356, 2022 | 11 | 2022 |
| Augmenting existing deterioration indices with chest radiographs to predict clinical deterioration E Mu, S Jabbour, AV Dalca, J Guttag, J Wiens, MW Sjoding PLoS One 17 (2), e0263922, 2022 | 8 | 2022 |
| Recent advances, applications, and open challenges in machine learning for health: Reflections from research roundtables at ml4h 2023 symposium H Jeong, S Jabbour, Y Yang, R Thapta, H Mozannar, WJ Han, ... arXiv preprint arXiv:2403.01628, 2024 | 5 | 2024 |
| Recent Advances, Applications and Open Challenges in Machine Learning for Health: Reflections from Research Roundtables at ML4H 2024 Symposium A Adibi, X Cao, Z Ji, JN Kaur, W Chen, E Healey, B Nuwagira, W Ye, ... arXiv preprint arXiv:2502.06693, 2025 | 3 | 2025 |
| DEPICT: Diffusion-Enabled Permutation Importance for Image Classification Tasks S Jabbour, G Kondas, E Kazerooni, M Sjoding, D Fouhey, J Wiens European Conference on Computer Vision, 35-51, 2024 | 2 | 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 | 2 | 2023 |
| On the limits of selective AI prediction: a case study in clinical decision making S Jabbour, D Fouhey, N Banovic, SD Shepard, E Kazerooni, MW Sjoding, ... arXiv preprint arXiv:2508.07617, 2025 | 1 | 2025 |
| Evaluation Framework for AI Systems in" the Wild" S Jabbour, T Chang, AD Antar, J Peper, I Jang, J Liu, JW Chung, S He, ... arXiv preprint arXiv:2504.16778, 2025 | 1 | 2025 |
| Machine Learning for Health (ML4H) 2024 H Zhou, S Hegselmann, E Healey, T Chang, C Ellington, M Leone, ... | | 2024 |
| 350. Joint Modeling of EHR and CXR Data to Predict COVID-19 Deterioration E Mu, S Jabbour, M Sjoding, J Guttag, J Wiens, A Dalca Open Forum Infectious Diseases 8 (Suppl 1), S279, 2021 | | 2021 |
| Combining chest X-rays and EHR data using machine learning to diagnose acute respiratory failure. S Jabbour, D Fouhey, E Kazerooni, J Wiens, MW Sjoding CoRR, 2021 | | 2021 |
Jenna WiensUniversity of MichiganVerified email at umich.edu
