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  2023 (2)
Multi-label Few-shot ICD Coding as Autoregressive Generation with Prompt. Yang, Z.; Sunjae, K.; Yao, Z.; and Yu, H. In Washington DC USA, February 2023. AAAI 2023
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Facilitate Communication between Physicians and Patients - the NoteAid Project. Yao, Z.; Wei, G.; Yang, Z.; Cao, Y.; Duan, Z.; Liu, W.; and Yu, H. March 2023. AMIA 2023 Informatics Summit, submitted.
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  2022 (23)
An Investigation of Socical Determinants of Health in UMLS. Rawat, B. P. S.; and Yu, H. In Houston TX USA, May 2022. AMIA Clinical Informatics 2022
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Generating Coherent Narratives with Subtopic Planning to Answer How-to Questions. Cai, P.; Yu, M.; Liu, F.; and Yu, H. In Abu Dhabi, December 2022. The GEM Workshop at EMNLP 2022
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Parameter Efficient Transfer Learning for Suicide Attempt and Ideation Detection. Rawat, B. P. S.; and Yu, H. In Abu Dhabi, December 2022. LOUHI 2022
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UMass A&P: An Assessment and Plan Reasoning System of UMass in the 2022 N2C2 Challenge. Kwon, S.; Yang, Z.; and Yu, H. November 2022. 2022 n2c2 Workshop, Washington DC
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Knowledge Injected Prompt Based Fine-tuning for Multi-label Few-shot ICD Coding. Yang, Z.; Wang, S.; Rawat, B. P. S.; Mitra, A.; and Yu, H. In Abu Dhabi, December 2022. Findings of the Association for Computational Linguistics: EMNLP 2022
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MedJEx: A Medical Jargon Extraction Model with Wiki's Hyperlink Span and Contextualized Masked Language Model Score. Kwon, S.; Yao, Z.; Jordan, H. S.; Levy, D. A.; Corner, B.; and Yu, H. In Abu Dhabi, December 2022. EMNLP 2022
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Racial differences in receipt of medications for opioid use disorder before and during the COVID-19 pandemic in the Veterans Health Administration. Sung, M. L.; Li, W.; León, C.; Reisman, J.; Liu, W.; Kerns, R. D.; Yu, H.; and Becker, W. C. November 2022. APHA 2022 Annual Meeting and Expo, Boston MA
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Using Machine Learning to Predict Opioid Overdose Using Electronic Health Record. Wang, X.; Li, R.; Druhl, E.; Li, W.; Sung, M. L.; Kerns, R. D.; Becker, W. C.; and Yu, H. November 2022. APHA 2022 Annual Meeting and Expo, Boston MA
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Automatically Detecting Opioid-Related Aberrant Behaviors from Electronic Health Records. Wang, X.; Li, R.; Lingeman, J. M.; Druhl, E.; Li, W.; Sung, M. L.; Kerns, R. D.; Becker, W. C.; and Yu, H. November 2022. APHA 2022 Annual Meeting and Expo, Boston MA
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An Investigation of the Representation of Social Determinants of Health in the UMLS. Rawat, B. P. S.; Keating, H.; Goodwin, R.; Druhl, E. B.; and Yu, H. In Washington, D.C., November 2022. AMIA 2022 Annual Symposium
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Generation of Patient After-Visit Summaries to Support Physicians. Cai, P.; Liu, F.; Bajracharya, A.; Liu, W.; Berlowitz, D.; Sills, J.; Kapoor, A.; Pradhan, R.; Levy, D.; and Yu, H. In Gyeongju, Republic of Korea, October 2022. COLING 2022
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Extracting Biomedical Factual Knowledge Using Pretrained Language Model and Electronic Health Record Context. Zonghai, Y.; Cao, Y.; Yang, Z.; Deshpande, V.; and Yu, H. In Washington, D.C., November 2022. AMIA 2022 Annual Symposium
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Pretraining of Patient Representations On Structured Electronic Health Records for Patient Outcome Prediction: case study as self-harm screening tool. Yang, Z.; and Hong, Y. In Washington DC USA, June 2022. ARM2022
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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. C.; Smelson, D. A.; and Yu, H. In Washington DC USA, June 2022. ARM 2022
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SBDH and Suicide: A Multi-Task Learning Framework for SBDH Detection in Electronic Health Records Using NLP. Mitra, A.; Rawat, B. P. S.; Druhl, E. B.; Keating, H.; Goodwin, R.; Hu, W.; Liu, W.; Tsai, J.; Smelson, D. A.; and Yu, H. In Washington DC USA, June 2022. ARM 2022
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Studying Association of Traumatic Brain Injury and Posttraumatic Stress Disorder Diagnoses with Hospitalized Self-Harm Among US Veterans, 2008-2017. Rawat, B. P. S.; Reisman, J.; Rongali, S.; Liu, W.; Yu, H.; and Carlson, K. In Washington DC USA, June 2022. ARM 2022 (Poster)
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NLP and Annie App for Social Determinants of Health. Mahapatra, S.; Chen, H.; Tsai, J.; and Yu, H. In Houston TX USA, May 2022. AMIA Clinical Informatics 2022
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EASE: A Tool to Extract Social Determinants of Health from Electronic Health Records. Rawat, B. P. S.; and Yu, H. In Houston TX USA, May 2022. AMIA Clinical Informatics 2022 (System Demo)
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The association of prescribed long-acting versus short-acting opioids and mortality among older adults. Sung, M.; Smirnova, J.; Li, W.; Liu, W.; Kerns, R. D.; Reisman, J. I.; Yu, H.; and Becker, W. C. In Society of General Internal Medicine Annual National Meeting, Orlando, Florida, USA, April 2022.
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Learning as Conversation: Dialogue Systems Reinforced for Information Acquisition. Cai, P.; Wan, H.; Liu, F.; Yu, M.; Yu, H.; and Joshi, S. In Seattle WA, USA, July 2022. NAACL 2022
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EHR Cohort Development Using Natural Language Processing For Identifying Symptoms Of Alzheimer's Disease. Yu, H.; Mitra, A.; Keating, H.; Liu, W.; Hu, W.; Xia, W.; Morin, P.; Berlowitz, D. R.; Bray, M.; Monfared, A.; and Zhang, Q. In Barcelona, Spain (Online), March 2022. AD/PD 2022
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ScAN: Suicide Attempt and Ideation Events Dataset. Rawat, B. P. S.; Kovaly, S.; Pigeon, W. R.; and Yu, H. In Seattle WA, USA, July 2022. NAACL 2022
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Using data science to improve outcomes for persons with opioid use disorder. Hayes, C. J.; Cucciare, M. A.; Martin, B. C.; Hudson, T. J.; Bush, K.; Lo-Ciganic, W.; Yu, H.; Charron, E.; and Gordon, A. J. Substance Abuse, 43(1): 956–963. 2022.
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  2021 (10)
SBDH and Suicide: A Multi-task Learning Framework for SBDH in Electronic Health Records. Mitra, A.; Rawat, B. P. S.; Druhl, E.; Keating, H.; Goodwin, R.; Hu, W.; Liu, W.; Tsai, J.; Smelson, D. A.; and Yu, H. In Online, October 2021. SciNLP 2021
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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: 391–413. August 2021.
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Membership Inference Attack Susceptibility of Clinical Language Models. Jagannatha, A.; Rawat, B. P. S.; and Yu, H. CoRR, abs/2104.08305. 2021. arXiv: 2104.08305
Membership Inference Attack Susceptibility of Clinical Language Models [link]Paper   link   bibtex   abstract  
Guideline-discordant dosing of direct-acting oral anticoagulants in the veterans health administration. Rose, A. J.; Lee, J. S.; Berlowitz, D. R.; Liu, W.; Mitra, A.; and Yu, H. BMC Health Services Research, 21(1): 1351. December 2021.
Guideline-discordant dosing of direct-acting oral anticoagulants in the veterans health administration [link]Paper   doi   link   bibtex   abstract  
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 Yu, H. JMIR medical informatics, 9(11): e32851. November 2021.
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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.
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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 (15)
Improved Pretraining for Domain-specific Contextual Embedding Models. Rongali, S.; Jagannatha, A.; Rawat, B. P. S.; and Yu, H. CoRR, abs/2004.02288. 2020. arXiv: 2004.02288
Improved Pretraining for Domain-specific Contextual Embedding Models [link]Paper   link   bibtex  
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 (17)
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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  2017 (9)
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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  2016 (7)
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.
link   bibtex   abstract  
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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  2015 (5)
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  
  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  
Automatically Recognizing Medication and Adverse Event Information From Food and Drug Administration’s Adverse Event Reporting System Narratives. Polepalli Ramesh, B.; Belknap, S. M; Li, Z.; Frid, N.; West, D. P; and Yu, H. JMIR Medical Informatics, 2(1): e10. June 2014.
Automatically Recognizing Medication and Adverse Event Information From Food and Drug Administration’s Adverse Event Reporting System Narratives [link]Paper   doi   link   bibtex  
A robust data-driven approach for gene ontology annotation. Li, Y.; and Yu, H. Database: The Journal of Biological Databases and Curation, 2014: bau113. 2014. 00000
A robust data-driven approach for gene ontology annotation [link]Paper   doi   link   bibtex   abstract  
  2013 (2)
Systems for Improving Electronic Health Record Note Comprehension. Polepalli Ramesh, B.; and Yu, H. In ACM SIGIR Workshop on Health Search & Discovery, 2013.
Systems for Improving Electronic Health Record Note Comprehension [pdf]Paper   link   bibtex   abstract  
CiteGraph: A Citation Network System for MEDLINE Articles and Analysis. Qing, Z.; and Hong, Y. Studies in Health Technology and Informatics,832–836. 2013.
CiteGraph: A Citation Network System for MEDLINE Articles and Analysis [link]Paper   doi   link   bibtex   abstract  
  2012 (2)
Beyond Captions: Linking Figures with Abstract Sentences in Biomedical Articles. Bockhorst, J. P.; Conroy, J. M.; Agarwal, S.; O’Leary, D. P.; and Yu, H. PLoS ONE, 7(7): e39618. July 2012.
Beyond Captions: Linking Figures with Abstract Sentences in Biomedical Articles [link]Paper   doi   link   bibtex  
Automatic discourse connective detection in biomedical text. Ramesh, B. P.; Prasad, R.; Miller, T.; Harrington, B.; and Yu, H. Journal of the American Medical Informatics Association: JAMIA, 19(5): 800–808. October 2012.
doi   link   bibtex   abstract  
  2011 (12)
AskHERMES: An online question answering system for complex clinical questions. Cao, Y.; Liu, F.; Simpson, P.; Antieau, L.; Bennett, A.; Cimino, J. J; Ely, J.; and Yu, H. Journal of Biomedical Informatics, 44(2): 277–288. April 2011.
AskHERMES: An online question answering system for complex clinical questions [link]Paper   doi   link   bibtex   abstract  
BioN∅T: A searchable database of biomedical negated sentences. Agarwal, S.; Yu, H.; and Kohane, I. BMC Bioinformatics, 12(1): 420. 2011.
BioN∅T: A searchable database of biomedical negated sentences [link]Paper   doi   link   bibtex  
Toward automated consumer question answering: Automatically separating consumer questions from professional questions in the healthcare domain. Liu, F.; Antieau, L. D.; and Yu, H. Journal of Biomedical Informatics, 44(6): 1032–1038. December 2011.
Toward automated consumer question answering: Automatically separating consumer questions from professional questions in the healthcare domain [link]Paper   doi   link   bibtex   abstract  
Simple and efficient machine learning frameworks for identifying protein-protein interaction relevant articles and experimental methods used to study the interactions. Agarwal, S.; Liu, F.; and Yu, H. BMC Bioinformatics, 12(Suppl 8): S10. 2011.
Simple and efficient machine learning frameworks for identifying protein-protein interaction relevant articles and experimental methods used to study the interactions [link]Paper   doi   link   bibtex   abstract  
Parsing citations in biomedical articles using conditional random fields. Zhang, Q.; Cao, Y.; and Yu, H. Computers in Biology and Medicine, 41(4): 190–194. April 2011.
Parsing citations in biomedical articles using conditional random fields [link]Paper   doi   link   bibtex   abstract  
Figure Text Extraction in Biomedical Literature. Kim, D.; and Yu, H. PLoS ONE, 6(1): e15338. January 2011.
Figure Text Extraction in Biomedical Literature [link]Paper   doi   link   bibtex  
Automatic figure classification in bioscience literature. Kim, D.; Ramesh, B. P.; and Yu, H. Journal of Biomedical Informatics, 44(5): 848–858. October 2011.
Automatic figure classification in bioscience literature [link]Paper   doi   link   bibtex  
An investigation into the feasibility of spoken clinical question answering. Miller, T.; Ravvaz, K.; Cimino, J. J.; and Yu, H. AMIA ... Annual Symposium proceedings. AMIA Symposium, 2011: 954–959. 2011.
An investigation into the feasibility of spoken clinical question answering [link]Paper   link   bibtex   abstract  
Apixaban versus warfarin in patients with atrial fibrillation. Granger, C. B.; Alexander, J. H.; McMurray, J. J. V.; Lopes, R. D.; Hylek, E. M.; Hanna, M.; Al-Khalidi, H. R.; Ansell, J.; Atar, D.; Avezum, A.; Bahit, M. C.; Diaz, R.; Easton, J. D.; Ezekowitz, J. A.; Flaker, G.; Garcia, D.; Geraldes, M.; Gersh, B. J.; Golitsyn, S.; Goto, S.; Hermosillo, A. G.; Hohnloser, S. H.; Horowitz, J.; Mohan, P.; Jansky, P.; Lewis, B. S.; Lopez-Sendon, J. L.; Pais, P.; Parkhomenko, A.; Verheugt, F. W. A.; Zhu, J.; Wallentin, L.; ARISTOTLE Committees; and Investigators The New England Journal of Medicine, 365(11): 981–992. September 2011.
Apixaban versus warfarin in patients with atrial fibrillation [link]Paper   doi   link   bibtex   abstract  
Figure summarizer browser extensions for PubMed Central. Agarwal, S.; and Yu, H. Bioinformatics, 27(12): 1723–1724. June 2011.
Figure summarizer browser extensions for PubMed Central [link]Paper   doi   link   bibtex  
The biomedical discourse relation bank. Prasad, R.; McRoy, S.; Frid, N.; Joshi, A.; and Yu, H. BMC Bioinformatics, 12(1): 188. May 2011.
The biomedical discourse relation bank [link]Paper   doi   link   bibtex   abstract  
Towards spoken clinical-question answering: evaluating and adapting automatic speech-recognition systems for spoken clinical questions. Liu, F.; Tur, G.; Hakkani-Tür, D.; and Yu, H. Journal of the American Medical Informatics Association: JAMIA, 18(5): 625–630. October 2011.
Towards spoken clinical-question answering: evaluating and adapting automatic speech-recognition systems for spoken clinical questions [link]Paper   doi   link   bibtex   abstract  
  2010 (7)
Lancet: a high precision medication event extraction system for clinical text. Li, Z.; Liu, F.; Antieau, L.; Cao, Y.; and Yu, H. Journal of the American Medical Informatics Association: JAMIA, 17(5): 563–567. October 2010.
Lancet: a high precision medication event extraction system for clinical text [link]Paper   doi   link   bibtex   abstract  
Identifying discourse connectives in biomedical text. Ramesh, B. P.; and Yu, H. AMIA ... Annual Symposium proceedings. AMIA Symposium, 2010: 657–661. November 2010.
Identifying discourse connectives in biomedical text [link]Paper   link   bibtex   abstract  
Biomedical negation scope detection with conditional random fields. Agarwal, S.; and Yu, H. Journal of the American Medical Informatics Association: JAMIA, 17(6): 696–701. November 2010. 00033 PMID: 20962133 PMCID: PMC3000754
Biomedical negation scope detection with conditional random fields [link]Paper   doi   link   bibtex   abstract  
Automatic Figure Ranking and User Interfacing for Intelligent Figure Search. Yu, H.; Liu, F.; and Ramesh, B. P. PLoS ONE, 5(10): e12983. October 2010.
Automatic Figure Ranking and User Interfacing for Intelligent Figure Search [link]Paper   doi   link   bibtex  
An IR-aided machine learning framework for the BioCreative II.5 Challenge. Cao, Y.; Li, Z.; Liu, F.; Agarwal, S.; Zhang, Q.; and Yu, H. IEEE/ACM Transactions on Computational Biology and Bioinformatics / IEEE, ACM, 7(3): 454–461. September 2010.
An IR-aided machine learning framework for the BioCreative II.5 Challenge [link]Paper   doi   link   bibtex   abstract  
Automatically extracting information needs from complex clinical questions. Best Paper in International Medical Informatics Association (IMIA) Yearbook 2011. Cao, Y.; Cimino, J. J; Ely, J.; and Yu, H. Journal of Biomedical Informatics. July 2010.
Automatically extracting information needs from complex clinical questions. Best Paper in International Medical Informatics Association (IMIA) Yearbook 2011 [link]Paper   doi   link   bibtex   abstract  
Detecting hedge cues and their scope in biomedical text with conditional random fields. Agarwal, S.; and Yu, H. Journal of Biomedical Informatics, 43(6): 953–961. December 2010.
doi   link   bibtex   abstract  
  2009 (8)
Using the Weighted Keyword Model to Improve Information Retrieval for Answering Biomedical Questions. Yu, H.; and Cao, Y. Summit on translational bioinformatics, 2009: 143. 2009.
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Investigating and annotating the role of citation in biomedical full-text articles. Yu, H.; Agarwal, S.; and Frid, N. In Bioinformatics and Biomedicine Workshop, pages 308–313, November 2009. IEEE
Investigating and annotating the role of citation in biomedical full-text articles [link]Paper   doi   link   bibtex   abstract  
Evaluating the weighted-keyword model to improve clinical question answering. Cao, Y.; Ely, J.; and Yu, H. In Bioinformatics and Biomedicine Workshop, pages 331–335, November 2009. IEEE INSPEC Accession Number: 10975550
Evaluating the weighted-keyword model to improve clinical question answering [link]Paper   doi   link   bibtex   abstract  
Automatically classifying sentences in full-text biomedical articles into Introduction, Methods, Results and Discussion. Agarwal, S.; and Yu, H. Bioinformatics, 25(23): 3174–3180. December 2009.
Automatically classifying sentences in full-text biomedical articles into Introduction, Methods, Results and Discussion [link]Paper   doi   link   bibtex  
Are figure legends sufficient? Evaluating the contribution of associated text to biomedical figure comprehension. Yu, H.; Agarwal, S.; Johnston, M.; and Cohen, A. Journal of Biomedical Discovery and Collaboration, 4(1): 1. 2009.
Are figure legends sufficient? Evaluating the contribution of associated text to biomedical figure comprehension [link]Paper   doi   link   bibtex   abstract  
Evaluation of the clinical question answering presentation. Cao, Y.; Ely, J.; Antieau, L.; and Yu, H. In Proceedings of the Workshop on Current Trends in Biomedical Natural Language Processing, pages 171, 2009. Association for Computational Linguistics
Evaluation of the clinical question answering presentation [link]Paper   doi   link   bibtex  
FigSum: automatically generating structured text summaries for figures in biomedical literature. Agarwal, S.; and Yu, H. AMIA ... Annual Symposium proceedings. AMIA Symposium, 2009: 6–10. November 2009.
FigSum: automatically generating structured text summaries for figures in biomedical literature [link]Paper   link   bibtex   abstract  
Hierarchical image classification in the bioscience literature. Kim, D.; and Yu, H. AMIA ... Annual Symposium proceedings. AMIA Symposium, 2009: 327–331. November 2009.
Hierarchical image classification in the bioscience literature [link]Paper   link   bibtex   abstract  
  2008 (3)
Translating biology: text mining tools that work. Cohen, K B.; Yu, H.; Bourne, P. E; and Hirschman, L. In Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing, volume 13, pages 551, 2008. NIHMSID: NIHMS92147
Translating biology: text mining tools that work [pdf]Paper   link   bibtex  
A pilot annotation to investigate discourse connectivity in biomedical text. Yu, H.; Frid, N.; McRoy, S.; Prasad, R.; Lee, A.; and Joshi, A. In Proceedings of the Workshop on Current Trends in Biomedical Natural Language Processing, pages 92–93, 2008. Association for Computational Linguistics
A pilot annotation to investigate discourse connectivity in biomedical text [pdf]Paper   link   bibtex  
Automatically extracting information needs from Ad Hoc clinical questions. Yu, H.; and Cao, Y. AMIA ... Annual Symposium proceedings. AMIA Symposium,96–100. November 2008.
Automatically extracting information needs from Ad Hoc clinical questions [link]Paper   link   bibtex   abstract  
  2007 (5)
Development, implementation, and a cognitive evaluation of a definitional question answering system for physicians. Yu, H.; Lee, M.; Kaufman, D.; Ely, J.; Osheroff, J. A.; Hripcsak, G.; and Cimino, J. Journal of Biomedical Informatics, 40(3): 236–251. June 2007.
Development, implementation, and a cognitive evaluation of a definitional question answering system for physicians [link]Paper   doi   link   bibtex  
Using MEDLINE as a knowledge source for disambiguating abbreviations and acronyms in full-text biomedical journal articles. Yu, H.; Kim, W.; Hatzivassiloglou, V.; and Wilbur, W. J. Journal of Biomedical Informatics, 40(2): 150–159. April 2007.
Using MEDLINE as a knowledge source for disambiguating abbreviations and acronyms in full-text biomedical journal articles [link]Paper   doi   link   bibtex   abstract  
The efficacy and safety of apixaban, an oral, direct factor Xa inhibitor, as thromboprophylaxis in patients following total knee replacement. Lassen, M. R.; Davidson, B. L.; Gallus, A.; Pineo, G.; Ansell, J.; and Deitchman, D. Journal of Thrombosis and Haemostasis, 5(12): 2368–2375. December 2007.
The efficacy and safety of apixaban, an oral, direct factor Xa inhibitor, as thromboprophylaxis in patients following total knee replacement [link]Paper   doi   link   bibtex   abstract  
A cognitive evaluation of four online search engines for answering definitional questions posed by physicians. Yu, H.; and Kaufman, D. Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing,328–339. 2007.
A cognitive evaluation of four online search engines for answering definitional questions posed by physicians [pdf]Paper   link   bibtex   abstract  
Frontiers of biomedical text mining: current progress. Zweigenbaum, P.; Demner-Fushman, D.; Yu, H.; and Cohen, K. B Briefings in Bioinformatics, 8(5): 358–75. September 2007.
Frontiers of biomedical text mining: current progress [link]Paper   doi   link   bibtex   abstract  
  2006 (7)
The semantics of a definiendum constrains both the lexical semantics and the lexicosyntactic patterns in the definiens. Yu, H.; and Wei, Y. In Proceedings of the BioNLP Workshop on Linking Natural Language Processing and Biology at HLT-NAACL, pages 1–8, New York, USA, 2006.
The semantics of a definiendum constrains both the lexical semantics and the lexicosyntactic patterns in the definiens [link]Paper   link   bibtex  
Towards answering biological questions with experimental evidence: automatically identifying text that summarize image content in full-text articles. Yu, H. AMIA ... Annual Symposium proceedings. AMIA Symposium,834–838. 2006.
Towards answering biological questions with experimental evidence: automatically identifying text that summarize image content in full-text articles [link]Paper   link   bibtex   abstract  
Accessing bioscience images from abstract sentences. Yu, H.; and Lee, M. Bioinformatics, 22(14): e547–e556. July 2006. 00039 PMID: 16873519
Accessing bioscience images from abstract sentences [link]Paper   doi   link   bibtex   abstract  
Beyond information retrieval–medical question answering. Lee, M.; Cimino, J.; Zhu, H. R.; Sable, C.; Shanker, V.; Ely, J.; and Yu, H. AMIA ... Annual Symposium proceedings. AMIA Symposium,469–473. 2006.
Beyond information retrieval–medical question answering [link]Paper   link   bibtex   abstract  
BioEx: a novel user-interface that accesses images from abstract sentences. Yu, H.; and Lee, M. In Proceedings of the Human Language Technology Conference of the NAACL, Companion Volume: Short Papers, pages 189–192, 2006. Association for Computational Linguistics
BioEx: a novel user-interface that accesses images from abstract sentences [link]Paper   link   bibtex  
Exploring supervised and unsupervised methods to detect topics in biomedical text. Lee, M.; Wang, W.; and Yu, H. BMC bioinformatics, 7: 140. March 2006.
Exploring supervised and unsupervised methods to detect topics in biomedical text [link]Paper   doi   link   bibtex   abstract  
Exploring text and image features to classify images in bioscience literature. Rafkind, B.; Lee, M.; Chang, S.; and Yu, H. In Proceedings of the HLT-NAACL BioNLP Workshop on Linking Natural Language and Biology, pages 73, 2006. Association for Computational Linguistics
Exploring text and image features to classify images in bioscience literature [link]Paper   doi   link   bibtex  
  2004 (2)
Using MEDLINE as a knowledge source for disambiguating abbreviations in full-text biomedical journal articles. Yu, H.; Kim, W.; Hatzivassiloglou, V.; and John Wilbur, W In Computer-Based Medical Systems, 2004. CBMS 2004. Proceedings. 17th IEEE Symposium on, pages 27–32, June 2004. IEEE
doi   link   bibtex   abstract  
GeneWays: a system for extracting, analyzing, visualizing, and integrating molecular pathway data. Rzhetsky, A.; Iossifov, I.; Koike, T.; Krauthammer, M.; Kra, P.; Morris, M.; Yu, H.; Duboué, P. A.; Weng, W.; Wilbur, W. J.; Hatzivassiloglou, V.; and Friedman, C. Journal of Biomedical Informatics, 37(1): 43–53. February 2004. 00251
doi   link   bibtex   abstract  
  2003 (2)
Extracting synonymous gene and protein terms from biological literature. Yu, H.; and Agichtein, E. Bioinformatics, 19(Suppl 1): i340–i349. July 2003.
Extracting synonymous gene and protein terms from biological literature [link]Paper   doi   link   bibtex   abstract  
Towards answering opinion questions: separating facts from opinions and identifying the polarity of opinion sentences. Yu, H.; and Hatzivassiloglou, V. In Proceedings of the 2003 conference on Empirical methods in natural language processing, volume 10, pages 129–136, 2003. Association for Computational Linguistics
Towards answering opinion questions: separating facts from opinions and identifying the polarity of opinion sentences [link]Paper   doi   link   bibtex  
  2002 (3)
Mapping Abbreviations to Full Forms in Biomedical Articles. Yu, H. Journal of the American Medical Informatics Association, 9(3): 262–272. May 2002.
Mapping Abbreviations to Full Forms in Biomedical Articles [link]Paper   doi   link   bibtex  
Automatic extraction of gene and protein synonyms from MEDLINE and journal articles. Yu, H.; Hatzivassiloglou, V.; Friedman, C.; Rzhetsky, A.; and Wilbur, W. J. Proceedings. AMIA Symposium,919–923. 2002.
Automatic extraction of gene and protein synonyms from MEDLINE and journal articles [link]Paper   link   bibtex   abstract  
Automatically identifying gene/protein terms in MEDLINE abstracts. Yu, H.; Hatzivassiloglou, V.; Rzhetsky, A.; and Wilbur, W. J. Journal of Biomedical Informatics, 35(5-6): 322–330. December 2002.
Automatically identifying gene/protein terms in MEDLINE abstracts [link]Paper   link   bibtex   abstract  
  2001 (2)
Knowledge-based disambiguation of abbreviations. Yu, H. In Proceedings of the AMIA Symposium, pages 1067, 2001.
Knowledge-based disambiguation of abbreviations [pdf]Paper   link   bibtex  
GENIES: a natural-language processing system for the extraction of molecular pathways from journal articles. Friedman, C.; Kra, P.; Yu, H.; Krauthammer, M.; and Rzhetsky, A. Bioinformatics, 17(Suppl 1): S74–S82. June 2001. 00521
GENIES: a natural-language processing system for the extraction of molecular pathways from journal articles [link]Paper   doi   link   bibtex  
  2000 (1)
A large scale, cross-disease family health history data set. Yu, H.; and Hripcsak, G. Proceedings of the AMIA Symposium,1162. 2000. PMC2243911
A large scale, cross-disease family health history data set [pdf]Paper   link   bibtex  
  1999 (1)
Representing genomic knowledge in the UMLS semantic network. Yu, H.; Friedman, C.; Rhzetsky, A.; and Kra, P. Proceedings of the AMIA Symposium,181. 1999.
Representing genomic knowledge in the UMLS semantic network. [link]Paper   link   bibtex   abstract  
  1988 (1)
Sensitivity and Specificity of Three Methods of Detecting Adverse Drug Reactions. Berry, L. L.; Segal, R.; Sherrin, T. P.; and Fudge, K. A. American Journal of Hospital Pharmacy, 45(7): 1534–1539. July 1988.
Sensitivity and Specificity of Three Methods of Detecting Adverse Drug Reactions [link]Paper   doi   link   bibtex   abstract  
  undefined (2)
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