| Med-BERT: pretrained contextualized embeddings on large-scale structured electronic health records for disease prediction L Rasmy, Y Xiang, Z Xie, C Tao, D Zhi Nature: NPJ Digital Medicine, 2021 | 1029 | 2021 |
| Deep learning in clinical natural language processing: a methodical review S Wu, K Roberts, S Datta, J Du, Z Ji, Y Si, S Soni, Q Wang, Q Wei, Y Xiang, ... JAMIA, 0 | 535* | |
| ML-Net: multi-label classification of biomedical texts with deep neural networks J Du, Q Chen, Y Peng, Y Xiang, C Tao, Z Lu JAMIA, 2019 | 188 | 2019 |
| A study of deep learning approaches for medication and adverse drug event extraction from clinical text Q Wei, Z Ji, Z Li, J Du, J Wang, J Xu, Y Xiang, F Tiryaki, S Wu, Y Zhang, ... JAMIA, 2020 | 140 | 2020 |
| Ernie 3.0 titan: Exploring larger-scale knowledge enhanced pre-training for language understanding and generation S Wang, Y Sun, Y Xiang, Z Wu, S Ding, W Gong, S Feng, J Shang, Y Zhao, ... Technical Report, 2021 | 113 | 2021 |
| XA-BiLSTM: A deep learning approach for depression detection in imbalanced data Q Cong, Z Feng, F Li, Y Xiang, G Rao, C Tao BIBM, 2018 | 110 | 2018 |
| Public perception analysis of tweets during the 2015 measles outbreak: comparative study using convolutional neural network models J Du, L Tang, Y Xiang, D Zhi, J Xu, HY Song, C Tao JMIR, 2018 | 72 | 2018 |
| Mapping multi-modal brain connectome for brain disorder diagnosis via cross-modal mutual learning Y Yang, C Ye, X Guo, T Wu, Y Xiang, T Ma IEEE TMI, 2023 | 67 | 2023 |
| Multimodal Data Matters: Language Model Pre-Training Over Structured and Unstructured Electronic Health Records S Liu, X Wang, Y Hou, G Li, H Wang, H Xu, Y Xiang, B Tang IEEE JBHI, 2022 | 65 | 2022 |
| Accelerating diffusion models via pre-segmentation diffusion sampling for medical image segmentation X Guo, Y Yang, C Ye, S Lu, B Peng, H Huang, Y Xiang, T Ma IEEE ISBI, 2023 | 61 | 2023 |
| Answer selection in community question answering via attentive neural networks Y Xiang, Q Chen, X Wang, Y Qin IEEE Signal Processing Letters, 2017 | 61 | 2017 |
| Multi-channel fusion LSTM for medical event prediction using EHRs S Liu, X Wang, Y Xiang, H Xu, H Wang, B Tang JBI 127, 104011, 2022 | 57 | 2022 |
| Application of artificial intelligence and machine learning for HIV prevention interventions Y Xiang, J Du, K Fujimoto, F Li, J Schneider, C Tao The Lancet HIV 9 (1), e54-e62, 2022 | 55 | 2022 |
| Asthma exacerbation prediction and risk factor analysis based on a time-sensitive, attentive neural network: retrospective cohort study Y Xiang, H Ji, Y Zhou, F Li, J Du, L Rasmy, S Wu, WJ Zheng, H Xu, D Zhi, ... JMIR, 2020 | 52 | 2020 |
| Ensemble learning for heterogeneous large language models with deep parallel collaboration Y Huang, X Feng, B Li, Y Xiang, H Wang, T Liu, B Qin Advances in Neural Information Processing Systems 37, 119838-119860, 2024 | 46 | 2024 |
| Extracting postmarketing adverse events from safety reports in the vaccine adverse event reporting system (VAERS) using deep learning J Du, Y Xiang, M Sankaranarayanapillai, M Zhang, J Wang, Y Si, ... JAMIA, 2021 | 45 | 2021 |
| A space-embedding strategy for anomaly detection in multivariate time series Z Ji, Y Wang, K Yan, X Xie, Y Xiang, J Huang ESWA 206, 117892, 2022 | 43 | 2022 |
| Time event ontology (TEO): to support semantic representation and reasoning of complex temporal relations of clinical events F Li, J Du, Y He, HY Song, M Madkour, G Rao, Y Xiang, Y Luo, HW Chen, ... JAMIA, 2020 | 41 | 2020 |
| Exploiting adversarial transfer learning for adverse drug reaction detection from texts Z Li, Z Yang, L Luo, Y Xiang, H Lin JBI, 2020 | 41 | 2020 |
| Time-sensitive clinical concept embeddings learned from large electronic health records Y Xiang, J Xu, Y Si, Z Li, L Rasmy, Y Zhou, F Tiryaki, F Li, Y Zhang, Y Wu, ... BMC medical informatics and decision making, 2019 | 41 | 2019 |
Cui TaoDepartment of AI and Informatics, Mayo ClinicVerified email at mayo.edu
