| Prediction of hypotension events with physiologic vital sign signatures in the intensive care unit JH Yoon, V Jeanselme, A Dubrawski, M Hravnak, MR Pinsky, G Clermont Critical Care 24 (1), 1-9, 2020 | 62 | 2020 |
| Deep Parametric Time-to-Event Regression with Time-Varying Covariates C Nagpal, V Jeanselme, A Dubrawski Survival Prediction-Algorithms, Challenges and Applications, 184-193, 2021 | 48* | 2021 |
| Leveraging expert consistency to improve algorithmic decision support M De-Arteaga, V Jeanselme, A Dubrawski, A Chouldechova Management Science, 2025 | 36 | 2025 |
| Neural Fine-Gray: Monotonic neural networks for competing risks V Jeanselme, CH Yoon, B Tom, J Barrett Conference on Health, Inference, and Learning, 379-392, 2023 | 27 | 2023 |
| Neural Survival Clustering: Non-parametric mixture of neural networks for survival clustering V Jeanselme, B Tom, J Barrett Conference on Health, Inference, and Learning, 92-102, 2022 | 25 | 2022 |
| Imputation strategies under clinical presence: Impact on algorithmic fairness V Jeanselme, M De-Arteaga, Z Zhang, J Barrett, B Tom Machine Learning for Health, 12-34, 2022 | 18 | 2022 |
| riSCC: A personalized risk model for the development of poor outcomes in cutaneous squamous cell carcinoma A Jambusaria-Pahlajani, V Jeanselme, DM Wang, NA Ran, EE Granger, ... Journal of the American Academy of Dermatology, 2025 | 16 | 2025 |
| Review of Language Models for Survival Analysis V Jeanselme, N Agarwal, C Wang AAAI 2024 Spring Symposium on Clinical Foundation Models, 2024 | 14 | 2024 |
| Deepjoint: Robust survival modelling under clinical presence shift V Jeanselme, G Martin, N Peek, M Sperrin, B Tom, J Barrett arXiv preprint arXiv:2205.13481, 2022 | 7 | 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 |
| A case for federated learning: Enabling and leveraging inter-hospital collaboration S Caldas, V Jeanselme, G Clermont, MR Pinsky, A Dubrawski C33. QUALITY, PROCESSES, AND OUTCOMES IN ACUTE AND CRITICAL CARE, A4790-A4790, 2020 | 5 | 2020 |
| Meds decentralized, extensible validation (meds-dev) benchmark: Establishing reproducibility and comparability in ml for health A Kolo, C Pang, E Choi, E Steinberg, H Jeong, J Gallifant, JA Fries, ... Machine Learning For Health Conference, 2024 | 4 | 2024 |
| Constrained Clustering and Multiple Kernel Learning without Pairwise Constraint Relaxation B Boecking, V Jeanselme, A Dubrawski Advances in Data Analysis and Classification, 2022 | 4 | 2022 |
| Sex differences in post cardiac arrest discharge locations V Jeanselme, M De-Arteaga, J Elmer, SM Perman, A Dubrawski Resuscitation plus 8, 100185, 2021 | 4 | 2021 |
| FoMoH: A clinically meaningful foundation model evaluation for structured electronic health records C Pang, V Jeanselme, YS Choi, X Jiang, Z Jing, A Kashyap, Y Kobayashi, ... arXiv preprint arXiv:2505.16941, 2025 | 3 | 2025 |
| Clinical Presence: Impact on Predictive Modelling and Algorithmic Fairness V Jeanselme University of Cambridge, 2024 | 3 | 2024 |
| Impact of immunosuppression on cutaneous squamous cell carcinoma outcomes JC Klein, KT Shahwan, UB Petric, T Mallela, L Voller, E Ruiz, N Ran, ... Journal of the American Academy of Dermatology, 2025 | 1 | 2025 |
| Competing risks: Impact on risk estimation and algorithmic fairness V Jeanselme, B Tom, J Barrett arXiv preprint arXiv:2508.05435, 2025 | 1 | 2025 |
| Identifying treatment response subgroups in observational time-to-event data V Jeanselme, CH Yoon, F Falck, B Tom, J Barrett arXiv preprint arXiv:2408.03463, 2024 | 1 | 2024 |
| Robustness of Machine Learning Models for Hemorrhage Detection V Jeanselme, A Wertz, G Clermont, MR Pinsky, A Dubrawski D23. WHAT'S NEW IN NON-PULMONARY CRITICAL CARE?, A6320-A6320, 2020 | 1 | 2020 |
Artur DubrawskiCarnegie Mellon UniversityVerified email at cs.cmu.edu
