| A Generalizable, Data-Driven Approach to Predict Daily Risk of Clostridium difficile Infection at Two Large Academic Health Centers J Oh, M Makar, C Fusco, R McCaffrey, K Rao, EE Ryan, L Washer, ... infection control & hospital epidemiology 39 (4), 425-433, 2018 | 126 | 2018 |
| Using Machine Learning and the Electronic Health Record to Predict Complicated Clostridium difficile Infection BY Li, J Oh, VB Young, K Rao, J Wiens Open forum infectious diseases 6 (5), ofz186, 2019 | 63 | 2019 |
| Learning to exploit invariances in clinical time-series data using sequence transformer networks J Oh, J Wang, J Wiens Machine Learning for Healthcare Conference, 332-347, 2018 | 58 | 2018 |
| Learning credible models J Wang, J Oh, H Wang, J Wiens Proceedings of the 24th ACM SIGKDD International Conference on Knowledge …, 2018 | 43 | 2018 |
| Mind the Performance Gap: Examining Dataset Shift During Prospective Validation E Ötleş, J Oh, B Li, M Bochinski, H Joo, J Ortwine, E Shenoy, L Washer, ... arXiv preprint arXiv:2107.13964, 2021 | 18 | 2021 |
| Laraine Washer, Lauren R West, Vincent B Young, John Guttag, et al. A generalizable, data-driven approach to predict daily risk of clostridium difficile infection at two large … J Oh, M Makar, C Fusco, R McCaffrey, K Rao, EE Ryan Infection Control & Hospital Epidemiology (ICHE) 39 (4), 425-433, 2018 | 12 | 2018 |
| 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 | 10 | 2019 |
| Relaxed weight sharing: Effectively modeling time-varying relationships in clinical time-series J Oh, J Wang, S Tang, M Sjoding, J Wiens Machine Learning for Healthcare Conference (MLHC), 2019 | 7 | 2019 |
| Prospective evaluation of data-driven models to predict daily risk of Clostridioides difficile infection at 2 large academic health centers M Kamineni, EÖ Meng, J Oh, K Rao, VB Young, BY Li, LR West, ... Infection Control & Hospital Epidemiology, 1-4, 2022 | 2 | 2022 |
| HAN phase 3 impact and process evaluation report C Churchwell, M Sullivan, D Thompson, J Oh Nexant, Tech. Rep, 2014 | 2 | 2014 |
| A data-driven approach to predict daily risk ofClostridium difficileinfection at two large academic health centers M Makar, J Oh, C Fusco, J Marchesani, R McCaffrey, K Rao, E Ryan, ... Open Forum Infectious Diseases 4, 2017 | 1 | 2017 |
| 17. Comparative Assessment of a Machine Learning Model and Rectal Swab Surveillance to Predict Hospital Onset Clostridioides difficile E Ötleş, J Oh, A Patel, M Keidan, VB Young, K Rao, J Wiens Open Forum Infectious Diseases 8 (Supplement_1), S12-S12, 2021 | | 2021 |
| Deep Learning Models for Clinical Data: Addressing Task Specific Structure J Oh | | 2021 |
Jenna WiensUniversity of Michiganumich.edu의 이메일 확인됨
