Recognizing named entities in tweets X Liu, S Zhang, F Wei, M Zhou Proceedings of the 49th annual meeting of the association for computational …, 2011 | 648 | 2011 |
Unsupervised biomedical named entity recognition: Experiments with clinical and biological texts S Zhang, N Elhadad Journal of biomedical informatics 46 (6), 1088-1098, 2013 | 347 | 2013 |
Online cancer communities as informatics intervention for social support: conceptualization, characterization, and impact S Zhang, EOC Bantum, J Owen, S Bakken, N Elhadad Journal of the American Medical Informatics Association 24 (2), 451-459, 2017 | 124 | 2017 |
EliIE: An open-source information extraction system for clinical trial eligibility criteria T Kang, S Zhang, Y Tang, GW Hruby, A Rusanov, N Elhadad, C Weng Journal of the American Medical Informatics Association 24 (6), 1062-1071, 2017 | 118 | 2017 |
Label-aware double transfer learning for cross-specialty medical named entity recognition Z Wang, Y Qu, L Chen, J Shen, W Zhang, S Zhang, Y Gao, G Gu, K Chen, ... arXiv preprint arXiv:1804.09021, 2018 | 95 | 2018 |
Named entity recognition for tweets X Liu, F Wei, S Zhang, M Zhou ACM Transactions on Intelligent Systems and Technology (TIST) 4 (1), 1-15, 2013 | 91 | 2013 |
Longitudinal analysis of discussion topics in an online breast cancer community using convolutional neural networks S Zhang, E Grave, E Sklar, N Elhadad Journal of biomedical informatics 69, 1-9, 2017 | 73 | 2017 |
Speculation detection for Chinese clinical notes: impacts of word segmentation and embedding models S Zhang, T Kang, X Zhang, D Wen, N Elhadad, J Lei Journal of biomedical informatics 60, 334-341, 2016 | 47 | 2016 |
Characterizing the sublanguage of online breast cancer forums for medications, symptoms, and emotions N Elhadad, S Zhang, P Driscoll, S Brody AMIA Annual Symposium Proceedings 2014, 516, 2014 | 41 | 2014 |
Detection of medical text semantic similarity based on convolutional neural network T Zheng, Y Gao, F Wang, C Fan, X Fu, M Li, Y Zhang, S Zhang, H Ma BMC medical informatics and decision making 19, 1-11, 2019 | 39 | 2019 |
We make choices we think are going to save us: Debate and stance identification for online breast cancer CAM discussions S Zhang, L Qiu, F Chen, W Zhang, Y Yu, N Elhadad Proceedings of the 26th International Conference on World Wide Web Companion …, 2017 | 39 | 2017 |
Does sustained participation in an online health community affect sentiment? S Zhang, E Bantum, J Owen, N Elhadad AMIA Annual Symposium Proceedings 2014, 1970, 2014 | 38 | 2014 |
Improving the efficacy of the data entry process for clinical research with a natural language processing–driven medical information extraction system: Quantitative field research J Han, K Chen, L Fang, S Zhang, F Wang, H Ma, L Zhao, S Liu JMIR medical informatics 7 (3), e13331, 2019 | 23 | 2019 |
Adaptive multi-task transfer learning for Chinese word segmentation in medical text J Xing, K Zhu, S Zhang Proceedings of the 27th International Conference on Computational …, 2018 | 23 | 2018 |
A cascaded approach for Chinese clinical text de-identification with less annotation effort Z Jian, X Guo, S Liu, H Ma, S Zhang, R Zhang, J Lei Journal of biomedical informatics 73, 76-83, 2017 | 23 | 2017 |
Detecting negation and scope in Chinese clinical notes using character and word embedding T Kang, S Zhang, N Xu, D Wen, X Zhang, J Lei Computer methods and programs in biomedicine 140, 53-59, 2017 | 22 | 2017 |
Development of a consumer health vocabulary by mining health forum texts based on word embedding: semiautomatic approach G Gu, X Zhang, X Zhu, Z Jian, K Chen, D Wen, L Gao, S Zhang, F Wang, ... JMIR medical informatics 7 (2), e12704, 2019 | 17 | 2019 |
Factors contributing to dropping-out in an online health community: static and longitudinal analyses S Zhang, N Elhadad AMIA Annual Symposium Proceedings 2016, 2090, 2017 | 14 | 2017 |
Hedge detection and scope finding by sequence labeling with procedural feature selection S Zhang, H Zhao, G Zhou, BL Lu Proceedings of the Fourteenth Conference on Computational Natural Language …, 2010 | 14 | 2010 |
A novel hierarchical machine learning model for hospital-acquired venous thromboembolism risk assessment among multiple-departments H Ma, W Sheng, J Li, L Hou, J Yang, J Cai, W Xu, S Zhang Journal of Biomedical Informatics 122, 103892, 2021 | 11 | 2021 |