Hongfang Liu


Attention Neural Model for Temporal Relation Extraction
Sijia Liu | Liwei Wang | Vipin Chaudhary | Hongfang Liu
Proceedings of the 2nd Clinical Natural Language Processing Workshop

Neural network models have shown promise in the temporal relation extraction task. In this paper, we present the attention based neural network model to extract the containment relations within sentences from clinical narratives. The attention mechanism used on top of GRU model outperforms the existing state-of-the-art neural network models on THYME corpus in intra-sentence temporal relation extraction.


MayoNLP at SemEval 2017 Task 10: Word Embedding Distance Pattern for Keyphrase Classification in Scientific Publications
Sijia Liu | Feichen Shen | Vipin Chaudhary | Hongfang Liu
Proceedings of the 11th International Workshop on Semantic Evaluation (SemEval-2017)

In this paper, we present MayoNLP’s results from the participation in the ScienceIE share task at SemEval 2017. We focused on the keyphrase classification task (Subtask B). We explored semantic similarities and patterns of keyphrases in scientific publications using pre-trained word embedding models. Word Embedding Distance Pattern, which uses the head noun word embedding to generate distance patterns based on labeled keyphrases, is proposed as an incremental feature set to enhance the conventional Named Entity Recognition feature sets. Support vector machine is used as the supervised classifier for keyphrase classification. Our system achieved an overall F1 score of 0.67 for keyphrase classification and 0.64 for keyphrase classification and relation detection.


Staggered NLP-assisted refinement for Clinical Annotations of Chronic Disease Events
Stephen Wu | Chung-Il Wi | Sunghwan Sohn | Hongfang Liu | Young Juhn
Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16)

Domain-specific annotations for NLP are often centered on real-world applications of text, and incorrect annotations may be particularly unacceptable. In medical text, the process of manual chart review (of a patient’s medical record) is error-prone due to its complexity. We propose a staggered NLP-assisted approach to the refinement of clinical annotations, an interactive process that allows initial human judgments to be verified or falsified by means of comparison with an improving NLP system. We show on our internal Asthma Timelines dataset that this approach improves the quality of the human-produced clinical annotations.

On Developing Resources for Patient-level Information Retrieval
Stephen Wu | Tamara Timmons | Amy Yates | Meikun Wang | Steven Bedrick | William Hersh | Hongfang Liu
Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16)

Privacy concerns have often served as an insurmountable barrier for the production of research and resources in clinical information retrieval (IR). We believe that both clinical IR research innovation and legitimate privacy concerns can be served by the creation of intra-institutional, fully protected resources. In this paper, we provide some principles and tools for IR resource-building in the unique problem setting of patient-level IR, following the tradition of the Cranfield paradigm.

MayoNLP at SemEval-2016 Task 1: Semantic Textual Similarity based on Lexical Semantic Net and Deep Learning Semantic Model
Naveed Afzal | Yanshan Wang | Hongfang Liu
Proceedings of the 10th International Workshop on Semantic Evaluation (SemEval-2016)


Representing Clinical Diagnostic Criteria in Quality Data Model Using Natural Language Processing
Na Hong | Dingcheng Li | Yue Yu | Hongfang Liu | Christopher G. Chute | Guoqian Jiang
Proceedings of BioNLP 15


Evaluating the Use of Empirically Constructed Lexical Resources for Named Entity Recognition
Siddhartha Jonnalagadda | Trevor Cohen | Stephen Wu | Hongfang Liu | Graciela Gonzalez
Proceedings of the IWCS 2013 Workshop on Computational Semantics in Clinical Text (CSCT 2013)

Analysis of Cross-Institutional Medication Information Annotations in Clinical Notes
Sunghwan Sohn | Cheryl Clark | Scott Halgrim | Sean Murphy | Siddhartha Jonnalagadda | Kavishwar Wagholikar | Stephen Wu | Christopher Chute | Hongfang Liu
Proceedings of the IWCS 2013 Workshop on Computational Semantics in Clinical Text (CSCT 2013)

MayoClinicNLPCORE: Semantic representations for textual similarity
Stephen Wu | Dongqing Zhu | Ben Carterette | Hongfang Liu
Second Joint Conference on Lexical and Computational Semantics (*SEM), Volume 1: Proceedings of the Main Conference and the Shared Task: Semantic Textual Similarity


Dynamically Generating a Protein Entity Dictionary Using Online Resources
Hongfang Liu | Zhangzhi Hu | Cathy Wu
Proceedings of the ACL Interactive Poster and Demonstration Sessions


A Study of Text Categorization for Model Organism Databases
Hongfang Liu | Cathy Wu
HLT-NAACL 2004 Workshop: Linking Biological Literature, Ontologies and Databases