| A review of approaches to identifying patient phenotype cohorts using electronic health records C Shivade, P Raghavan, E Fosler-Lussier, PJ Embi, N Elhadad, ... Journal of the American Medical Informatics Association 21 (2), 221-230, 2014 | 557 | 2014 |
| Lessons from Natural Language Inference in the Clinical Domain A Romanov, C Shivade Proceedings of EMNLP 2018, 2018 | 238 | 2018 |
| Overview of the MEDIQA 2019 shared task on textual inference, question entailment and question answering AB Abacha, C Shivade, D Demner-Fushman Proceedings of the 18th BioNLP Workshop and Shared Task, 370-379, 2019 | 128 | 2019 |
| Towards building large-scale distributed systems for twitter sentiment analysis VN Khuc, C Shivade, R Ramnath, J Ramanathan Proceedings of the 27th Annual ACM Symposium on Applied Computing, 459-464, 2012 | 96 | 2012 |
| Diagnosis-specific readmission risk prediction using electronic health data: a retrospective cohort study C Hebert, C Shivade, R Foraker, J Wasserman, C Roth, H Mekhjian, ... BMC Medical Informatics and Decision Making 14 (1), 65, 2014 | 77 | 2014 |
| Overview of the MEDIQA 2021 shared task on summarization in the medical domain AB Abacha, Y M’rabet, Y Zhang, C Shivade, C Langlotz, ... Proceedings of the 20th Workshop on Biomedical Language Processing, 74-85, 2021 | 72 | 2021 |
| Textual inference for eligibility criteria resolution in clinical trials C Shivade, C Hebert, M Lopetegui, MC de Marneffe, E Fosler-Lussier, ... Journal of Biomedical Informatics, 2015 | 49 | 2015 |
| A quantitative and qualitative evaluation of sentence boundary detection for the clinical domain D Griffis, C Shivade, E Fosler-Lussier, AM Lai Proceedings of the AMIA Summits on Translational Science 2016, 88, 2016 | 46 | 2016 |
| Comparison of UMLS terminologies to identify risk of heart disease using clinical notes C Shivade, P Malewadkar, E Fosler-Lussier, AM Lai Journal of Biomedical Informatics 58, S103-S110, 2015 | 39 | 2015 |
| Neural Inverse Text Normalization M Sunkara, C Shivade, S Bodapati, K Kirchhoff Proceedings of ICASSP, 2021 | 36 | 2021 |
| Towards Automatic Generation of Shareable Synthetic Clinical Notes Using Neural Language Models O Melamud, C Shivade Proceedings of the ClinicalNLP workshop at NAACL-HLT 2019, 2019 | 35 | 2019 |
| Mednli-a natural language inference dataset for the clinical domain C Shivade Proceedings of the 2018 Conference on Empirical Methods in Natural Language …, 2019 | 29 | 2019 |
| Towards Visual Dialog for Radiology O Kovaleva, C Shivade, S Kashyap, K Kanjaria, J Wu, D Ballah, A Coy, ... Proceedings of BioNLP at ACL, 60-69, 2020 | 25 | 2020 |
| Determining appropriate medical image processing pipeline based on machine learning A Katouzian, A Pillai, C Shivade, M Bendersky, A Jadhav, V Mukherjee, ... US Patent 10,740,866, 2020 | 24 | 2020 |
| Leveraging medical visual question answering with supporting facts T Kornuta, D Rajan, C Shivade, A Asseman, AS Ozcan Proceedings of ImageCLEF 2019 VQA-Med, 2019 | 18 | 2019 |
| Extending NegEx with kernel methods for negation detection in clinical text C Shivade, MC de Marneffe, E Fosler-Lussier, AM Lai Proceedings of the ExProM workshop at NAACL-HLT 2015, 41-46, 2015 | 18 | 2015 |
| Towards clinical encounter summarization: Learning to compose discharge summaries from prior notes HC Shing, C Shivade, N Pourdamghani, F Nan, P Resnik, D Oard, ... arXiv preprint arXiv:2104.13498, 2021 | 17 | 2021 |
| Corpus-based discovery of semantic intensity scales C Shivade, MC de Marneffe, E Fosler-Lussier, A Lai Proceedings of NAACL-HLT 2015, 2015 | 17 | 2015 |
| Integrating population-and patient-level data for secondary use of electronic health records to study overweight and obesity. C Roth, CP Shivade, RE Foraker, PJ Embi Studies in health technology and informatics 192, 1100-1100, 2013 | 17 | 2013 |
| Deduplication of medical concepts from patient information TF Syeda-Mahmood, C Shivade US Patent 11,081,216, 2021 | 14 | 2021 |
Eric Fosler-LussierJohn Makhoul Professor of Computer Science & Engineering, The Ohio State University在 cse.ohio-state.edu 的电子邮件经过验证
