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18th BioNLP@ACL 2019: Florence, Italy
- Dina Demner-Fushman, Kevin Bretonnel Cohen, Sophia Ananiadou, Junichi Tsujii:
Proceedings of the 18th BioNLP Workshop and Shared Task, BioNLP@ACL 2019, Florence, Italy, August 1, 2019. Association for Computational Linguistics 2019, ISBN 978-1-950737-28-4 - Denis Newman-Griffis
, Ayah Zirikly, Guy Divita, Bart Desmet:
Classifying the reported ability in clinical mobility descriptions. 1-10 - Steven Kester Yuwono, Hwee Tou Ng, Kee Yuan Ngiam:
Learning from the Experience of Doctors: Automated Diagnosis of Appendicitis Based on Clinical Notes. 11-19 - Sarvesh Soni, Kirk Roberts:
A Paraphrase Generation System for EHR Question Answering. 20-29 - Geeticka Chauhan
REflex: Flexible Framework for Relation Extraction in Multiple Domains. 30-47 - Mark Ormerod, Jesús Martínez del Rincón
Analysing Representations of Memory Impairment in a Clinical Notes Classification Model. 48-57 - Yifan Peng, Shankai Yan, Zhiyong Lu:
Transfer Learning in Biomedical Natural Language Processing: An Evaluation of BERT and ELMo on Ten Benchmarking Datasets. 58-65 - Emilia Apostolova, Tony Wang, Tim Tschampel, Ioannis Koutroulis, Tom Velez:
Combining Structured and Free-text Electronic Medical Record Data for Real-time Clinical Decision Support. 66-70 - Maria Mitrofan, Verginica Barbu Mititelu
MoNERo: a Biomedical Gold Standard Corpus for the Romanian Language. 71-79 - Dheeraj Rajagopal, Nidhi Vyas, Aditya Siddhant, Anirudha Rayasam, Niket Tandon, Eduard H. Hovy:
Domain Adaptation of SRL Systems for Biological Processes. 80-87 - Qiao Jin
Deep Contextualized Biomedical Abbreviation Expansion. 88-96 - Hanna Pylieva, Artem N. Chernodub, Natalia Grabar, Thierry Hamon:
RNN Embeddings for Identifying Difficult to Understand Medical Words. 97-104 - Christopher R. Norman, Mariska M. G. Leeflang, René Spijker
A distantly supervised dataset for automated data extraction from diagnostic studies. 105-114 - Georgeta Bordea, Tsanta Randriatsitohaina, Fleur Mougin
Query selection methods for automated corpora construction with a use case in food-drug interactions. 115-124 - Billy Chiu, Simon Baker, Martha Palmer, Anna Korhonen:
Enhancing biomedical word embeddings by retrofitting to verb clusters. 125-134 - Aditya Joshi
A Comparison of Word-based and Context-based Representations for Classification Problems in Health Informatics. 135-141 - Julien Fauqueur, Ashok Thillaisundaram, Theodosia Togia:
Constructing large scale biomedical knowledge bases from scratch with rapid annotation of interpretable patterns. 142-151 - Leonardo Campillos Llanos
First Steps towards Building a Medical Lexicon for Spanish with Linguistic and Semantic Information. 152-164 - Xindi Wang
Incorporating Figure Captions and Descriptive Text in MeSH Term Indexing. 165-175 - Hrant Khachatrian, Lilit Nersisyan
BioRelEx 1.0: Biological Relation Extraction Benchmark. 176-190 - Heath Goodrum, Meghana Gudala, Ankita Misra, Kirk Roberts:
Extraction of Lactation Frames from Drug Labels and LactMed. 191-200 - Natalia Viani, Hegler Tissot, Ariane Bernardino, Sumithra Velupillai:
Annotating Temporal Information in Clinical Notes for Timeline Reconstruction: Towards the Definition of Calendar Expressions. 201-210 - Leonie Grön, Ann Bertels, Kris Heylen:
Leveraging Sublanguage Features for the Semantic Categorization of Clinical Terms. 211-216 - Hichem Mezaoui, Isuru Gunasekara, Aleksandr Gontcharov:
Enhancing PIO Element Detection in Medical Text Using Contextualized Embedding. 217-222 - Fábio Lopes
Contributions to Clinical Named Entity Recognition in Portuguese. 223-233 - Zhaodong Yan, Serena Jeblee, Graeme Hirst:
Can Character Embeddings Improve Cause-of-Death Classification for Verbal Autopsy Narratives? 234-239 - Zixu Wang, Julia Ive, Sumithra Velupillai, Lucia Specia
Is artificial data useful for biomedical Natural Language Processing algorithms? 240-249 - Yuanhe Tian, Weicheng Ma, Fei Xia, Yan Song:
ChiMed: A Chinese Medical Corpus for Question Answering. 250-260 - Sarah Wiegreffe, Edward Choi, Sherry Yan, Jimeng Sun, Jacob Eisenstein:
Clinical Concept Extraction for Document-Level Coding. 261-272 - Cyril Grouin, Natalia Grabar, Vincent Claveau, Thierry Hamon:
Clinical Case Reports for NLP. 273-282 - Dianbo Liu, Dmitriy Dligach, Timothy A. Miller:
Two-stage Federated Phenotyping and Patient Representation Learning. 283-291 - Manolis Kyriakakis, Ion Androutsopoulos, Artur Saudabayev, Joan Ginés i Ametllé:
Transfer Learning for Causal Sentence Detection. 292-297 - Sotiris Kotitsas, Dimitris Pappas
Embedding Biomedical Ontologies by Jointly Encoding Network Structure and Textual Node Descriptors. 298-308 - Anaïs Koptient, Rémi Cardon
Simplification-induced transformations: typology and some characteristics. 309-318 - Mark Neumann, Daniel King
ScispaCy: Fast and Robust Models for Biomedical Natural Language Processing. 319-327 - Zenan Zhai, Dat Quoc Nguyen, Saber A. Akhondi, Camilo Thorne
Improving Chemical Named Entity Recognition in Patents with Contextualized Word Embeddings. 328-338 - Hassan Alhuzali
Improving classification of Adverse Drug Reactions through Using Sentiment Analysis and Transfer Learning. 339-347 - Gaurav Vashisth, Jan-Niklas Voigt-Antons, Michael Mikhailov, Roland Roller:
Exploring Diachronic Changes of Biomedical Knowledge using Distributed Concept Representations. 348-358 - Anna Koroleva, Patrick Paroubek:
Extracting relations between outcomes and significance levels in Randomized Controlled Trials (RCTs) publications. 359-369 - Asma Ben Abacha, Chaitanya Shivade, Dina Demner-Fushman:
Overview of the MEDIQA 2019 Shared Task on Textual Inference, Question Entailment and Question Answering. 370-379 - Wei Zhu
PANLP at MEDIQA 2019: Pre-trained Language Models, Transfer Learning and Knowledge Distillation. 380-388 - Hemant Pugaliya, Karan Saxena, Shefali Garg, Sheetal Shalini, Prashant Gupta, Eric Nyberg, Teruko Mitamura:
Pentagon at MEDIQA 2019: Multi-task Learning for Filtering and Re-ranking Answers using Language Inference and Question Entailment. 389-398 - Yichong Xu, Xiaodong Liu, Chunyuan Li, Hoifung Poon, Jianfeng Gao:
DoubleTransfer at MEDIQA 2019: Multi-Source Transfer Learning for Natural Language Understanding in the Medical Domain. 399-405 - Jiin Nam, Seunghyun Yoon, Kyomin Jung:
Surf at MEDIQA 2019: Improving Performance of Natural Language Inference in the Clinical Domain by Adopting Pre-trained Language Model. 406-414 - Zhaofeng Wu, Yan Song, Sicong Huang, Yuanhe Tian, Fei Xia:
WTMED at MEDIQA 2019: A Hybrid Approach to Biomedical Natural Language Inference. 415-426 - Cemil Cengiz, Ulas Sert, Deniz Yuret:
KU_ai at MEDIQA 2019: Domain-specific Pre-training and Transfer Learning for Medical NLI. 427-436 - Huiwei Zhou, Xuefei Li, Weihong Yao, Chengkun Lang, Shixian Ning:
DUT-NLP at MEDIQA 2019: An Adversarial Multi-Task Network to Jointly Model Recognizing Question Entailment and Question Answering. 437-445 - Huiwei Zhou, Bizun Lei, Zhe Liu, Zhuang Liu:
DUT-BIM at MEDIQA 2019: Utilizing Transformer Network and Medical Domain-Specific Contextualized Representations for Question Answering. 446-452 - Vinayshekhar Bannihatti Kumar, Ashwin Srinivasan, Aditi Chaudhary, James Route, Teruko Mitamura, Eric Nyberg:
Dr.Quad at MEDIQA 2019: Towards Textual Inference and Question Entailment using contextualized representations. 453-461 - Sai Abishek Bhaskar, Rashi Rungta, James Route, Eric Nyberg, Teruko Mitamura:
Sieg at MEDIQA 2019: Multi-task Neural Ensemble for Biomedical Inference and Entailment. 462-470 - Prakhar Sharma, Sumegh Roychowdhury:
IIT-KGP at MEDIQA 2019: Recognizing Question Entailment using Sci-BERT stacked with a Gradient Boosting Classifier. 471-477 - Vincent Nguyen, Sarvnaz Karimi
ANU-CSIRO at MEDIQA 2019: Question Answering Using Deep Contextual Knowledge. 478-487 - Sahil Chopra, Ankita Gupta, Anupama Kaushik:
MSIT_SRIB at MEDIQA 2019: Knowledge Directed Multi-task Framework for Natural Language Inference in Clinical Domain. 488-492 - Noha S. Tawfik, Marco Spruit:
UU_TAILS at MEDIQA 2019: Learning Textual Entailment in the Medical Domain. 493-499 - William R. Kearns, Wilson Lau, Jason A. Thomas:
UW-BHI at MEDIQA 2019: An Analysis of Representation Methods for Medical Natural Language Inference. 500-509 - Kamal Raj Kanakarajan, Suriyadeepan Ramamoorthy, Vaidheeswaran Archana, Soham Chatterjee, Malaikannan Sankarasubbu:
Saama Research at MEDIQA 2019: Pre-trained BioBERT with Attention Visualisation for Medical Natural Language Inference. 510-516 - Dibyanayan Bandyopadhyay
IITP at MEDIQA 2019: Systems Report for Natural Language Inference, Question Entailment and Question Answering. 517-522 - Andre Lamurias
LasigeBioTM at MEDIQA 2019: Biomedical Question Answering using Bidirectional Transformers and Named Entity Recognition. 523-527 - Lung-Hao Lee, Yi Lu, Po-Han Chen, Po-Lei Lee, Kuo-Kai Shyu:
NCUEE at MEDIQA 2019: Medical Text Inference Using Ensemble BERT-BiLSTM-Attention Model. 528-532 - Anumeha Agrawal, Rosa Anil George, Selvan Sunitha Ravi
ARS_NITK at MEDIQA 2019: Analysing Various Methods for Natural Language Inference, Recognising Question Entailment and Medical Question Answering System. 533-540
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