| Bidirectional Recurrent Neural Networks for Medical Event Detection in Electronic Health Records A Jagannatha, H Yu arXiv preprint arXiv:1606.07953, 2016 | 392* | 2016 |
| Structured prediction models for RNN based sequence labeling in clinical text AN Jagannatha, H Yu Proceedings of the conference on empirical methods in natural language …, 2016 | 266 | 2016 |
| Overview of the first natural language processing challenge for extracting medication, indication, and adverse drug events from electronic health record notes (MADE 1.0) A Jagannatha, F Liu, W Liu, H Yu Drug safety 42, 99-111, 2019 | 158 | 2019 |
| Learning for biomedical information extraction: Methodological review of recent advances F Liu, J Chen, A Jagannatha, H Yu arXiv preprint arXiv:1606.07993, 2016 | 61 | 2016 |
| Towards drug safety surveillance and pharmacovigilance: current progress in detecting medication and adverse drug events from electronic health records F Liu, A Jagannatha, H Yu Drug safety 42 (1), 95-97, 2019 | 60 | 2019 |
| Membership inference attack susceptibility of clinical language models A Jagannatha, BPS Rawat, H Yu arXiv preprint arXiv:2104.08305, 2021 | 46 | 2021 |
| Mining and ranking biomedical synonym candidates from Wikipedia A Jagannatha, J Chen, H Yu Proceedings of the sixth international workshop on health text mining and …, 2015 | 34 | 2015 |
| Ranking medical terms to support expansion of lay language resources for patient comprehension of electronic health record notes: adapted distant supervision approach J Chen, AN Jagannatha, SJ Fodeh, H Yu JMIR medical informatics 5 (4), e8531, 2017 | 31 | 2017 |
| Calibrating structured output predictors for natural language processing A Jagannatha, H Yu Proceedings of the conference. Association for Computational Linguistics …, 2020 | 27 | 2020 |
| A hybrid neural network model for joint prediction of presence and period assertions of medical events in clinical notes L Rumeng, Y Hong AMIA Annual Symposium Proceedings 2017, 1149, 2017 | 23 | 2017 |
| Object-aware cropping for self-supervised learning S Mishra, A Shah, A Bansal, A Jagannatha, J Anjaria, A Sharma, ... arXiv preprint arXiv:2112.00319, 2021 | 22 | 2021 |
| AMIA Annual Symposium Proceedings J Li, KV Sarma, KC Ho, A Gertych, BS Knudsen, CW Arnold | 17 | 2017 |
| Hong Yu F Liu, A Jagannatha Learning for biomedical information extraction: Methodological review of …, 2016 | 17 | 2016 |
| Active learning for new domains in natural language understanding S Peshterliev, J Kearney, A Jagannatha, I Kiss, S Matsoukas arXiv preprint arXiv:1810.03450, 2018 | 15 | 2018 |
| Federated intrusion detection for iot with heterogeneous cohort privacy AK Chathoth, A Jagannatha, S Lee arXiv preprint arXiv:2101.09878, 2021 | 12 | 2021 |
| Continual domain-tuning for pretrained language models S Rongali, A Jagannatha, BPS Rawat, H Yu arXiv preprint arXiv:2004.02288, 2020 | 12 | 2020 |
| Inferring ADR causality by predicting the Naranjo Score from Clinical Notes BPS Rawat, A Jagannatha, F Liu, H Yu AMIA Annual Symposium Proceedings 2020, 1041, 2020 | 12 | 2020 |
| Towards automatic generation of questions from long answers SK Mishra, P Goel, A Sharma, A Jagannatha, D Jacobs, H Daumé III arXiv preprint arXiv:2004.05109, 2020 | 11 | 2020 |
| Towards High Confidence Off-Policy Reinforcement Learning for Clinical Applications A Jagannatha, P Thomas, H Yu | 10 | 2018 |
| Pose invariant face recognition based on hybrid-global linear regression RSA Abhishek Sharma, Anamika Dubey, A. N. Jagannatha Neural Computing and Applications 19 (8), 1227–1235, 2010 | 10 | 2010 |
