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  2021 (7)
Risk Factors Associated With Nonfatal Opioid Overdose Leading to Intensive Care Unit Admission: A Cross-sectional Study. Mitra, A.; Ahsan, H.; Li, W.; Liu, W.; Kerns, R. D; Tsai, J.; Becker, W.; Smelson, D. A; and Hong, Y. JMIR Medical Informatics, 9(11). 2021.
doi   link   bibtex   abstract  
Evaluating the Effectiveness of NoteAid in a Community Hospital Setting: Randomized Trial of Electronic Health Record Note Comprehension Interventions With Patients. Lalor, J. P; Hu, W.; Tran, M.; Wu, H.; Mazor, K. M; and Yu, H. Journal of Medical Internet Research, 23(5). 2021.
doi   link   bibtex   abstract  
MIMIC-SBDH: A Dataset for Social and Behavioral Determinants of Health. Ahsan, H.; Ohnuki, E.; Mitra, A.; and Yu, H. Proceedings of Machine Learning Research 149:1–20, 2021. 2021.
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Improving Formality Style Transfer with Context-Aware Rule Injection. Yao, Z.; and Yu, H. In Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers), pages 1561–1570, Online, August 2021. Association for Computational Linguistics
Improving Formality Style Transfer with Context-Aware Rule Injection [link]Paper   doi   link   bibtex   abstract  
Relation Classification for Bleeding Events From Electronic Health Records Using Deep Learning Systems: An Empirical Study. Mitra, A.; Rawat, B. P. S.; McManus, D. D.; and Yu, H. JMIR Medical Informatics, 9(7): e27527. July 2021. Company: JMIR Medical Informatics Distributor: JMIR Medical Informatics Institution: JMIR Medical Informatics Label: JMIR Medical Informatics Publisher: JMIR Publications Inc., Toronto, Canada
Relation Classification for Bleeding Events From Electronic Health Records Using Deep Learning Systems: An Empirical Study [link]Paper   doi   link   bibtex   abstract  
Epinoter: A Natural Language Processing Tool for Epidemiological Studies. Liu, W.; Li, F.; Jin, Y.; Granillo, E.; Yarzebski, J.; Li, W.; and Yu, H. In Proceedings of the 14th International Joint Conference on Biomedical Engineering Systems and Technologies, volume 5, pages 754–761, February 2021.
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Prevalence of Frailty and Associations with Oral Anticoagulant Prescribing in Atrial Fibrillation. Sanghai, S. R; Liu, W.; Wang, W.; Rongali, S.; Orkaby, A. R; Saczynski, J. S; Rose, A. J; Kapoor, A.; Li, W.; Yu, H.; and McManus, D. D Journal of General Internal Medicine. May 2021.
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  2020 (14)
Neural data-to-text generation with dynamic content planning. Chen, K.; Li, F.; Hu, B.; Peng, W.; Chen, Q.; Yu, H.; and Xiang, Y. Knowledge-Based Systems,106610. November 2020.
Neural data-to-text generation with dynamic content planning [link]Paper   doi   link   bibtex   abstract  
Bleeding Entity Recognition in Electronic Health Records: A Comprehensive Analysis of End-to-End Systems. Mitra, A.; Rawat, B. P. S.; McManus, D.; Kapoor, A.; and Yu, H. In AMIA Fall Symposium, pages 860–869, 2020.
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Inferring ADR causality by predicting the Naranjo Score from Clinical Notes. Rawat, B. P. S.; Jagannatha, A.; Liu, F.; and Yu, H. In AMIA Fall Symposium, pages 1041–1049, 2020.
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Calibrating Structured Output Predictors for Natural Language Processing. Jagannatha, A.; and Yu, H. In 2020 Annual Conference of the Association for Computational Linguistics (ACL), July 2020. NIHMSID: NIHMS1661932
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ICD Coding from Clinical Text Using Multi-­‐Filter Residual Convolutional Neural Network. Li, F.; and Yu, H. In The Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI-20), pages 8180–8187, New York City, New York, February 2020.
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Generating Medical Assessments Using a Neural Network Model: Algorithm Development and Validation. Hu, B.; Bajracharya, A.; and Yu, H. JMIR Medical Informatics, 8(1): e14971. 2020. Company: JMIR Medical Informatics Distributor: JMIR Medical Informatics Institution: JMIR Medical Informatics Label: JMIR Medical Informatics Publisher: JMIR Publications Inc., Toronto, Canada
Generating Medical Assessments Using a Neural Network Model: Algorithm Development and Validation [link]Paper   doi   link   bibtex   abstract  
BENTO: A Visual Platform for Building Clinical NLP Pipelines Based on CodaLab. Jin, Y.; Li, F.; and Yu, H. In 2020 Annual Conference of the Association for Computational Linguistics (ACL), pages 95–100, July 2020. NIHMSID: NIHMS1644629
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Dynamic Data Selection for Curriculum Learning via Ability Estimation. Lalor, J. P.; and Yu, H. In Findings of the Association for Computational Linguistics: EMNLP 2020, pages 545–555, Online, November 2020. Association for Computational Linguistics
Dynamic Data Selection for Curriculum Learning via Ability Estimation [link]Paper   link   bibtex   abstract  
Generating Accurate Electronic Health Assessment from Medical Graph. Yang, Z.; and Yu, H. In Findings of the Association for Computational Linguistics: EMNLP 2020, pages 3764–3773, Online, November 2020. Association for Computational Linguistics NIHMSID: NIHMS1658452
Generating Accurate Electronic Health Assessment from Medical Graph [link]Paper   link   bibtex   abstract  
Conversational machine comprehension: a literature review. Gupta, S.; Rawat, B. P. S.; and Yu, H. arXiv preprint arXiv:2006.00671,2739–2753. December 2020.
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Neural Data-to-Text Generation with Dynamic Content Planning. Chen, K.; Li, F.; Hu, B.; Peng, W.; Chen, Q.; and Yu, H. arXiv:2004.07426 [cs]. April 2020. arXiv: 2004.07426
Neural Data-to-Text Generation with Dynamic Content Planning [link]Paper   link   bibtex   abstract  
BENTO: A Visual Platform for Building Clinical NLP Pipelines Based on CodaLab. Jin, Y; Li, F; and Yu, H In AMIA Fall Symposium, 2020.
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Neural Multi-Task Learning for Adverse Drug Reaction Extraction. Liu, F; and Yu, H In AMIA Fall Symposium, 2020.
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Learning Latent Space Representations to Predict Patient Outcomes: Model Development and Validation. Rongali, S.; Rose, A. J.; McManus, D. D.; Bajracharya, A. S.; Kapoor, A.; Granillo, E.; and Yu, H. Journal of Medical Internet Research, 22(3): e16374. 2020. Company: Journal of Medical Internet Research Distributor: Journal of Medical Internet Research Institution: Journal of Medical Internet Research Label: Journal of Medical Internet Research Publisher: JMIR Publications Inc., Toronto, Canada
Learning Latent Space Representations to Predict Patient Outcomes: Model Development and Validation [link]Paper   doi   link   bibtex   abstract  
  2019 (19)
Fine-Tuning Bidirectional Encoder Representations From Transformers (BERT)–Based Models on Large-Scale Electronic Health Record Notes: An Empirical Study. Li, F.; Jin, Y.; Liu, W.; Rawat, B. P. S.; Cai, P.; and Yu, H. JMIR Medical Informatics, 7(3): e14830. September 2019.
Fine-Tuning Bidirectional Encoder Representations From Transformers (BERT)–Based Models on Large-Scale Electronic Health Record Notes: An Empirical Study [link]Paper   doi   link   bibtex  
Detecting Hypoglycemia Incidents Reported in Patients’ Secure Messages: Using Cost-Sensitive Learning and Oversampling to Reduce Data Imbalance. Chen, J.; Lalor, J.; Liu, W.; Druhl, E.; Granillo, E.; Vimalananda, V. G; and Yu, H. Journal of Medical Internet Research, 21(3). March 2019.
Detecting Hypoglycemia Incidents Reported in Patients’ Secure Messages: Using Cost-Sensitive Learning and Oversampling to Reduce Data Imbalance [link]Paper   doi   link   bibtex   abstract  
Automatic Detection of Hypoglycemic Events From the Electronic Health Record Notes of Diabetes Patients: Empirical Study. Jin, Y.; Li, F.; Vimalananda, V. G.; and Yu, H. JMIR Medical Informatics, 7(4): e14340. 2019.
Automatic Detection of Hypoglycemic Events From the Electronic Health Record Notes of Diabetes Patients: Empirical Study [link]Paper   doi   link   bibtex   abstract  
Learning to detect and understand drug discontinuation events from clinical narratives. Liu, F.; Pradhan, R.; Druhl, E.; Freund, E.; Liu, W.; Sauer, B. C.; Cunningham, F.; Gordon, A. J.; Peters, C. B.; and Yu, H. Journal of the American Medical Informatics Association, 26(10): 943–951. October 2019.
Learning to detect and understand drug discontinuation events from clinical narratives [link]Paper   doi   link   bibtex   abstract  
Overview of the First Natural Language Processing Challenge for Extracting Medication, Indication, and Adverse Drug Events from Electronic Health Record Notes (MADE 1.0). Jagannatha, A.; Liu, F.; Liu, W.; and Yu, H. Drug Safety, (1): 99–111. January 2019.
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Naranjo Question Answering using End-to-End Multi-task Learning Model. Rawat, B. P; Li, F.; and Yu, H. 25th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD),2547–2555. 2019.
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A neural abstractive summarization model guided with topic sentences. ICONIP. Chen, C.; Hu, B.; Chen, Q.; and Yu, H. In 2019.
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An investigation of single-domain and multidomain medication and adverse drug event relation extraction from electronic health record notes using advanced deep learning models. Li, F.; and Yu, H. Journal of the American Medical Informatics Association, 26(7): 646–654. July 2019.
An investigation of single-domain and multidomain medication and adverse drug event relation extraction from electronic health record notes using advanced deep learning models [link]Paper   doi   link   bibtex   abstract  
Anticoagulant prescribing for non-valvular atrial fibrillation in the Veterans Health Administration. Rose, A.; Goldberg, R; McManus, D.; Kapoor, A; Wang, V; Liu, W; and Yu, H Journal of the American Heart Association. 2019.
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Learning Latent Parameters without Human Response Patterns: Item Response Theory with Artificial Crowds. Lalor, J. P.; Wu, H.; and Yu, H. In Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP), pages 4240–4250, Hong Kong, China, November 2019. Association for Computational Linguistics NIHMSID: NIHMS1059054
Learning Latent Parameters without Human Response Patterns: Item Response Theory with Artificial Crowds [link]Paper   doi   link   bibtex   abstract  
Clinical Question Answering from Electronic Health Records. In the MLHC 2019 research track proceedings. Singh, B.; Li, F.; and Yu, H. In The MLHC 2019 research track proceedings, 2019.
Clinical Question Answering from Electronic Health Records. In the MLHC 2019 research track proceedings [pdf]Paper   link   bibtex  
Comparing Human and DNN-Ensemble Response Patterns for Item Response Theory Model Fitting. Lalor, J.; Wu, H.; and Yu, H. 2019 Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)The Workshop on Cognitive Modeling and Computational Linguistics (CMCL). 2019.
Comparing Human and DNN-Ensemble Response Patterns for Item Response Theory Model Fitting [pdf]Paper   link   bibtex  
QuikLitE, a Framework for Quick Literacy Evaluation in Medicine: Development and Validation. Zheng, J.; and Yu, H. Journal of Medical Internet Research, 21(2): e12525. 2019.
QuikLitE, a Framework for Quick Literacy Evaluation in Medicine: Development and Validation [link]Paper   doi   link   bibtex   abstract  
Towards Drug Safety Surveillance and Pharmacovigilance: Current Progress in Detecting Medication and Adverse Drug Events from Electronic Health Records. Liu, F.; Jagannatha, A.; and Yu, H. Drug Safety. January 2019.
Towards Drug Safety Surveillance and Pharmacovigilance: Current Progress in Detecting Medication and Adverse Drug Events from Electronic Health Records [link]Paper   doi   link   bibtex  
Improving Electronic Health Record Note Comprehension With NoteAid: Randomized Trial of Electronic Health Record Note Comprehension Interventions With Crowdsourced Workers. Lalor, J. P.; Woolf, B.; and Yu, H. Journal of Medical Internet Research, 21(1): e10793. 2019.
Improving Electronic Health Record Note Comprehension With NoteAid: Randomized Trial of Electronic Health Record Note Comprehension Interventions With Crowdsourced Workers [link]Paper   doi   link   bibtex   abstract  
Generating Classical Chinese Poems from Vernacular Chinese. Yang, Z.; Cai, P.; Feng, Y.; Li, F.; Feng, W.; Chiu, E. S.; and yu , h. In Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP), pages 6156–6165, Hong Kong, China, November 2019. Association for Computational Linguistics
Generating Classical Chinese Poems from Vernacular Chinese [link]Paper   doi   link   bibtex   abstract  
Method for Meta-Level Continual Learning. Yu, H.; and Munkhdalai, T. January 2019.
Method for Meta-Level Continual Learning [link]Paper   link   bibtex   abstract  
Advancing Clinical Research Through Natural Language Processing on Electronic Health Records: Traditional Machine Learning Meets Deep Learning. Liu, F.; Weng, C.; and Yu, H. In Richesson, R. L.; and Andrews, J. E., editor(s), Clinical Research Informatics, of Health Informatics, pages 357–378. Springer International Publishing, Cham, 2019.
Advancing Clinical Research Through Natural Language Processing on Electronic Health Records: Traditional Machine Learning Meets Deep Learning [link]Paper   doi   link   bibtex   abstract  
Automatic extraction of quantitative data from ClinicalTrials.gov to conduct meta-analyses. Pradhan, R.; Hoaglin, D. C.; Cornell, M.; Liu, W.; Wang, V.; and Yu, H. Journal of Clinical Epidemiology, 105: 92–100. January 2019.
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  2018 (20)
Clinical Relation Extraction Toward Drug Safety Surveillance Using Electronic Health Record Narratives: Classical Learning Versus Deep Learning. Munkhdalai, T.; Liu, F.; and Yu, H. JMIR public health and surveillance, 4(2): e29. April 2018.
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A Natural Language Processing System That Links Medical Terms in Electronic Health Record Notes to Lay Definitions: System Development Using Physician Reviews. Chen, J.; Druhl, E.; Polepalli Ramesh, B.; Houston, T. K.; Brandt, C. A.; Zulman, D. M.; Vimalananda, V. G.; Malkani, S.; and Yu, H. Journal of Medical Internet Research, 20(1): e26. January 2018.
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A hybrid Neural Network Model for Joint Prediction of Presence and Period Assertions of Medical Events in Clinical Notes. Rumeng, L.; Abhyuday N, J.; and Hong, Y. AMIA Annual Symposium Proceedings, 2017: 1149–1158. April 2018.
A hybrid Neural Network Model for Joint Prediction of Presence and Period Assertions of Medical Events in Clinical Notes [link]Paper   link   bibtex   abstract  
Assessing Readability of Medical Documents: A Ranking Approach. Zheng, J.; and Yu, H The Journal of Medical Internet Research Medical Informatics. March 2018.
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Understanding Deep Learning Performance through an Examination of Test Set Difficulty: A Psychometric Case Study. Lalor, J.; Wu, H.; Munkhdalai, T.; and Yu, H. In EMNLP, 2018.
Understanding Deep Learning Performance through an Examination of Test Set Difficulty: A Psychometric Case Study [link]Paper   doi   link   bibtex   abstract  
Soft Label Memorization-Generalization for Natural Language Inference. Lalor, J.; Wu, H.; and Yu, H. In 2018.
Soft Label Memorization-Generalization for Natural Language Inference. [link]Paper   link   bibtex   abstract  
Sentence Simplification with Memory-Augmented Neural Networks. Vu, T.; Hu, B.; Munkhdalai, T.; and Yu, H. In North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2018.
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Recent Trends In Oral Anticoagulant Use and Post-Discharge Complications Among Atrial Fibrillation Patients With Acute Myocardial Infarction. Amartya Kundu; Kevin O ’Day; Darleen M. Lessard; Joel M. Gore1; Steven A. Lubitz; Hong Yu; Mohammed W. Akhter; Daniel Z. Fisher; Robert M. Hayward Jr.; Nils Henninger; Jane S. Saczynski; Allan J. Walkey; Alok Kapoor; Jorge Yarzebski; Robert J. Goldberg; and David D. McManus In 2018. Journal of Atrial Fibrillation
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ComprehENotes: An Instrument to Assess Patient EHR Note Reading Comprehension of Electronic Health Record Notes: Development and Validation. Lalor, J; Wu, H; Chen, L; Mazor, K; and Yu, H The Journal of Medical Internet Research. April 2018.
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Detecting Hypoglycemia Incidence from Patients’ Secure Messages. Chen, J; and Yu, H In 2018.
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Extraction of Information Related to Adverse Drug Events from Electronic Health Record Notes: Design of an End-to-End Model Based on Deep Learning. Li, F.; Liu, W.; and Yu, H. JMIR medical informatics, 6(4): e12159. November 2018.
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Reference Standard Development to Train Natural Language Processing Algorithms to Detect Problematic Buprenorphine-Naloxone Therapy. Celena B Peters; Fran Cunningham; Adam Gordon; Hong Yu; Cedric Salone; Jessica Zacher; Ronald Carico; Jianwei Leng; Nikolh Durley; Weisong Liu; Chao-Chin Lu; Emily Druhl; Feifan Liu; and Brian C Sauer In VA Pharmacy Informatics Conference 2018, 2018.
Reference Standard Development to Train Natural Language Processing Algorithms to Detect Problematic Buprenorphine-Naloxone Therapy [link]Paper   link   bibtex  
Inadequate diversity of information resources searched in US-affiliated systematic reviews and meta-analyses: 2005-2016. Pradhan, R.; Garnick, K.; Barkondaj, B.; Jordan, H. S.; Ash, A.; and Yu, H. Journal of Clinical Epidemiology, 102: 50–62. October 2018.
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Assessing the Readability of Medical Documents: A Ranking Approach. Zheng, J.; and Yu, H. JMIR medical informatics, 6(1): e17. March 2018.
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ComprehENotes, an Instrument to Assess Patient Reading Comprehension of Electronic Health Record Notes: Development and Validation. Lalor, J. P.; Wu, H.; Chen, L.; Mazor, K. M.; and Yu, H. Journal of Medical Internet Research, 20(4): e139. April 2018.
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Recent Trends in Oral Anticoagulant Use and Post-Discharge Complications Among Atrial Fibrillation Patients with Acute Myocardial Infarction. Kundu, A.; Day, K. O.; Lessard, D. M.; Gore, J. M.; Lubitz, S. A.; Yu, H.; Akhter, M. W.; Fisher, D. Z.; Hayward, R. M.; Henninger, N.; Saczynski, J. S.; Walkey, A. J.; Kapoor, A.; Yarzebski, J.; Goldberg, R. J.; and McManus, D. D. Journal of Atrial Fibrillation, 10(5): 1749. February 2018.
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Accuracy of International Classification of Disease Clinical Modification Codes for Detecting Bleeding Events in Electronic Health Records and When to Use Them. Wang, V; McManus, D; Ash, A; Hoaglin, D; and Yu, H In 2018.
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Frontiers of Clinical Information Extraction: Current Progress in Medication and Adverse Drug Event Detection from Electronic Health Records. Abhyuday Jagannatha; Feifan Liu; Weisong Liu; and Hong Yu In 9th Annual Pharmacy Informatics Conference, 2018.
Frontiers of Clinical Information Extraction: Current Progress in Medication and Adverse Drug Event Detection from Electronic Health Records [link]Paper   link   bibtex  
Panel – Deep Learning for Healthcare - Hype or the Real Thing?. J. Sun; B. Westover; H. Yu; D. Sontag; and M. Ghassemi In AMIA 2018 Informatics Summit, 2018.
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Panel - Frontiers of Clinical Information Extraction: Current Progress in Medication and Adverse Drug Event Detection from Electronic Health Records. Feifan Liu; Abhyuday Jagannatha; and Hong Yu In AMIA 2018 Informatics Summit, 2018.
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  2017 (13)
Meta Networks. Munkhdalai, T.; and Yu, H. In ICML, volume 70, pages 2554–2563, Sydney, Australia, August 2017.
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Neural Semantic Encoders. Munkhdalai, T; and Yu, H. In European Chapter of the Association for Computational Linguistics 2017 (EACL), volume 1, pages 397–407, April 2017.
Neural Semantic Encoders [pdf]Paper   link   bibtex   abstract  
Detecting Opioid-Related Aberrant Behavior using Natural Language Processing. Lingeman, J. M.; Wang, P.; Becker, W.; and Yu, H. AMIA ... Annual Symposium proceedings. AMIA Symposium, 2017: 1179–1185. 2017.
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CIFT: Crowd-Informed Fine-Tuning to Improve Machine Learning Ability. Lalor, J; Wu, H; and Yu, H In February 2017.
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Assessing Electronic Health Record Readability. Zheng, J; and Yu, H In 2017.
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Reasoning with memory augmented neural networks for language comprehension. Munkhdalai, T.; and Yu, H. 5th International Conference on Learning Representations (ICLR). 2017.
Reasoning with memory augmented neural networks for language comprehension. [link]Paper   link   bibtex   abstract  
Readability Formulas and User Perceptions of Electronic Health Records Difficulty: A Corpus Study. Zheng, J.; and Yu, H. Journal of Medical Internet Research, 19(3): e59. 2017.
Readability Formulas and User Perceptions of Electronic Health Records Difficulty: A Corpus Study [link]Paper   doi   link   bibtex   abstract  
Neural Tree Indexers for Text Understanding. Munkhdalai, T.; and Yu, H. In Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 1, Long Papers, pages 11–21, Valencia, Spain, April 2017. Association for Computational Linguistics
Neural Tree Indexers for Text Understanding [link]Paper   link   bibtex   abstract  
Generating a Test of Electronic Health Record Narrative Comprehension with Item Response Theory. Lalor, J; Wu, H; Chen, L; Mazor, K; and Yu, H In November 2017.
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An Analysis of Ability in Deep Neural Networks. Lalor, J. P.; Wu, H.; Munkhdalai, T.; and Yu, H. arXiv preprint arXiv:1702.04811. 2017.
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Ranking Medical Terms to Support Expansion of Lay Language Resources for Patient Comprehension of Electronic Health Record Notes: Adapted Distant Supervision Approach. Chen, J.; Jagannatha, A. N.; Fodeh, S. J.; and Yu, H. JMIR medical informatics, 5(4): e42. October 2017.
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Improving Machine Learning Ability with Fine-Tuning. Lalor, J.; Wu, H.; and Yu, H. In ICML, 2017.
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An Analysis of Machine Learning Intelligence. Lalor, J. P.; Wu, H.; Munkhdalai, T.; and Yu, H. arXiv:1702.04811 [cs]. February 2017. arXiv: 1702.04811
An Analysis of Machine Learning Intelligence [link]Paper   link   bibtex   abstract  
  2016 (9)
Structured prediction models for RNN based sequence labeling in clinical text. Jagannatha, A. N.; and Yu, H. In Proceedings of the Conference on Empirical Methods in Natural Language Processing, volume 2016, pages 856–865, November 2016.
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RETAIN: An Interpretable Predictive Model for Healthcare using Reverse Time Attention Mechanism. Choi, E.; Bahadori, M. T.; Sun, J.; Kulas, J.; Schuetz, A.; and Stewart, W. In Advances in Neural Information Processing Systems, pages 3504–3512, 2016.
RETAIN: An Interpretable Predictive Model for Healthcare using Reverse Time Attention Mechanism [link]Paper   link   bibtex  
Learning to Rank Scientific Documents from the Crowd. Lingeman, J. M; and Yu, H. arXiv:1611.01400. November 2016.
Learning to Rank Scientific Documents from the Crowd [pdf]Paper   link   bibtex   abstract  
Learning for Biomedical Information Extraction: Methodological Review of Recent Advances. Liu, F.; Chen, J.; Jagannatha, A.; and Yu, H. arXiv:1606.07993. June 2016.
Learning for Biomedical Information Extraction: Methodological Review of Recent Advances [pdf]Paper   link   bibtex   abstract  
Citation Analysis with Neural Attention Models. Munkhdalai, M; Lalor, J; and Yu, H In Proceedings of the Seventh International Workshop on Health Text Mining and Information Analysis (LOUHI) ,, pages 69–77, Austin, TX, November 2016. Association for Computational Linguistics
Citation Analysis with Neural Attention Models [pdf]Paper   doi   link   bibtex  
Condensed Memory Networks for Clinical Diagnostic Inferencing. Prakash, A.; Zhao, S.; Hasan, S. A.; Datla, V.; Lee, K.; Qadir, A.; Liu, J.; and Farri, O. arXiv:1612.01848 [cs]. December 2016. arXiv: 1612.01848
Condensed Memory Networks for Clinical Diagnostic Inferencing [link]Paper   link   bibtex   abstract  
Finding Important Terms for Patients in Their Electronic Health Records: A Learning-to-Rank Approach Using Expert Annotations. Chen, J.; Zheng, J.; and Yu, H. JMIR medical informatics, 4(4): e40. November 2016.
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EHR Note Paraphrasing for NoteAid Evaluation. Yu, H. In SBM, 2016.
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Mismatch between Patient Information-Seeking and Physician Expectation at a Diabetes Outpatient Clinic. Yu, H.; Makkapati, S.; Maranda, L.; and Malkani, S. In SBM, 2016.
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  2015 (8)
Translating Electronic Health Record Notes from English to Spanish: A Preliminary Study. Liu, W.; Cai, S.; Balaji, R.; Chiriboga, G.; Knight, K.; and Yu, H. In ACL-IJCNLP, pages 134, Bei Jing, China, July 2015.
Translating Electronic Health Record Notes from English to Spanish: A Preliminary Study [pdf]Paper   doi   link   bibtex  
Figure-Associated Text Summarization and Evaluation. Polepalli Ramesh, B.; Sethi, R. J.; and Yu, H. PLOS ONE, 10(2): e0115671. February 2015.
Figure-Associated Text Summarization and Evaluation [link]Paper   doi   link   bibtex  
DeTEXT: A Database for Evaluating Text Extraction from Biomedical Literature Figures. Yin, X.; Yang, C.; Pei, W.; Man, H.; Zhang, J.; Learned-Miller, E.; and Yu, H. PLoS ONE, 10(5). May 2015.
DeTEXT: A Database for Evaluating Text Extraction from Biomedical Literature Figures [link]Paper   doi   link   bibtex   abstract  
Methods for Linking EHR Notes to Education Materials. Zheng, J.; and Yu, H. AMIA Joint Summits on Translational Science proceedings AMIA Summit on Translational Science, 2015: 209–215. 2015.
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Identifying Key Concepts from EHR Notes Using Domain Adaptation. Zheng, J.; Yu, H.; and Bedford, M. A. In SIXTH INTERNATIONAL WORKSHOP ON HEALTH TEXT MINING AND INFORMATION ANALYSIS (LOUHI), pages 115, 2015.
Identifying Key Concepts from EHR Notes Using Domain Adaptation [link]Paper   link   bibtex  
Improving Concept Identification for linking EHR notes to education materials. Zheng, J; and Yu, H. In Empirical Methods in Natural Language Processing, Lisboa, Portugal, 2015.
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Towards Mining Electronic Health Records for Opioid ADE Surveillance. Yu, H; Brandt, C; Becker, W; and Kem, R In The 2015 HSR&D/QUERI National Conference, 2015.
Towards Mining Electronic Health Records for Opioid ADE Surveillance [link]Paper   link   bibtex   abstract  
Learning to rank scientific articles. Lingerman, J; and Hong, Y. In AMIA Fall Symposium, 2015.
Learning to rank scientific articles. [pdf]Paper   link   bibtex  
  2014 (4)
Learning to Rank Figures within a Biomedical Article. Liu, F.; and Yu, H. PLoS ONE, 9(3): e61567. March 2014.
Learning to Rank Figures within a Biomedical Article [link]Paper   doi   link   bibtex   abstract  
Computational Approaches for Predicting Biomedical Research Collaborations. Zhang, Q.; and Yu, H. PLoS ONE, 9(11): e111795. November 2014.
Computational Approaches for Predicting Biomedical Research Collaborations [link]Paper   doi   link   bibtex   abstract