| { | |
| "paper_id": "2020", | |
| "header": { | |
| "generated_with": "S2ORC 1.0.0", | |
| "date_generated": "2023-01-19T12:27:35.482626Z" | |
| }, | |
| "title": "0:15-10:25 BERT-XML: Large Scale Automated ICD Coding Using BERT Pretraining", | |
| "authors": [ | |
| { | |
| "first": "Zachariah", | |
| "middle": [], | |
| "last": "Zhang", | |
| "suffix": "", | |
| "affiliation": {}, | |
| "email": "" | |
| }, | |
| { | |
| "first": "Jingshu", | |
| "middle": [], | |
| "last": "Liu", | |
| "suffix": "", | |
| "affiliation": {}, | |
| "email": "" | |
| }, | |
| { | |
| "first": "Narges", | |
| "middle": [], | |
| "last": "Razavian", | |
| "suffix": "", | |
| "affiliation": {}, | |
| "email": "" | |
| } | |
| ], | |
| "year": "", | |
| "venue": null, | |
| "identifiers": {}, | |
| "abstract": "", | |
| "pdf_parse": { | |
| "paper_id": "2020", | |
| "_pdf_hash": "", | |
| "abstract": [], | |
| "body_text": [ | |
| { | |
| "text": "This volume contains papers from the 3rd Workshop on Clinical Natural Language Processing (ClinicalNLP), held at EMNLP 2020.", | |
| "cite_spans": [], | |
| "ref_spans": [], | |
| "eq_spans": [], | |
| "section": "Introduction", | |
| "sec_num": null | |
| }, | |
| { | |
| "text": "Clinical text offers unique challenges that differentiate it not only from open-domain data, but from other types of text in the biomedical domain as well. Notably, clinical text contains a significant number of abbreviations, medical terms, and other clinical jargon. Clinical narratives are characterized by nonstandard document structures that are often critical to overall understanding. Narrative provider notes are designed to communicate with other experts while at the same time serving as a legal record. Finally, clinical notes contain sensitive patient-specific information that raise privacy and security concerns that present special challenges for natural language systems. This workshop focuses on the work that develops methods to address the above challenges, with the goal of advancing state-of-the-art in clinical NLP.", | |
| "cite_spans": [], | |
| "ref_spans": [], | |
| "eq_spans": [], | |
| "section": "Introduction", | |
| "sec_num": null | |
| } | |
| ], | |
| "back_matter": [], | |
| "bib_entries": { | |
| "BIBREF0": { | |
| "ref_id": "b0", | |
| "title": "MeDAL: Medical Abbreviation Disambiguation Dataset for Natural Language Understanding Pretrain", | |
| "authors": [ | |
| { | |
| "first": "Xing", | |
| "middle": [], | |
| "last": "Ing Zhi Wen", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "Han", | |
| "middle": [], | |
| "last": "Lu", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "Siva", | |
| "middle": [], | |
| "last": "Reddy", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": ".", | |
| "middle": [ | |
| "." | |
| ], | |
| "last": "", | |
| "suffix": "" | |
| } | |
| ], | |
| "year": null, | |
| "venue": "", | |
| "volume": "", | |
| "issue": "", | |
| "pages": "", | |
| "other_ids": {}, | |
| "num": null, | |
| "urls": [], | |
| "raw_text": "MeDAL: Medical Abbreviation Disambiguation Dataset for Natural Language Understanding Pretrain- ing Zhi Wen, Xing Han Lu and Siva Reddy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 130", | |
| "links": null | |
| }, | |
| "BIBREF1": { | |
| "ref_id": "b1", | |
| "title": "Knowledge Grounded Conversational Symptom Detection with Graph Memory Networks Hongyin Luo", | |
| "authors": [ | |
| { | |
| "first": "Wen", | |
| "middle": [], | |
| "last": "Shang", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "James", | |
| "middle": [], | |
| "last": "Li", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": ".", | |
| "middle": [ | |
| "." | |
| ], | |
| "last": "Glass", | |
| "suffix": "" | |
| } | |
| ], | |
| "year": null, | |
| "venue": "", | |
| "volume": "", | |
| "issue": "", | |
| "pages": "", | |
| "other_ids": {}, | |
| "num": null, | |
| "urls": [], | |
| "raw_text": "Knowledge Grounded Conversational Symptom Detection with Graph Memory Networks Hongyin Luo, Shang-Wen Li and James Glass . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 136", | |
| "links": null | |
| }, | |
| "BIBREF2": { | |
| "ref_id": "b2", | |
| "title": "Pretrained Language Models for Biomedical and Clinical Tasks: Understanding and Extending the State-of-the-Art Patrick Lewis", | |
| "authors": [ | |
| { | |
| "first": "Myle", | |
| "middle": [], | |
| "last": "Ott", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "Jingfei", | |
| "middle": [], | |
| "last": "Du", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": ".", | |
| "middle": [ | |
| "." | |
| ], | |
| "last": "Veselin Stoyanov", | |
| "suffix": "" | |
| } | |
| ], | |
| "year": null, | |
| "venue": "", | |
| "volume": "", | |
| "issue": "", | |
| "pages": "", | |
| "other_ids": {}, | |
| "num": null, | |
| "urls": [], | |
| "raw_text": "Pretrained Language Models for Biomedical and Clinical Tasks: Understanding and Extending the State-of-the-Art Patrick Lewis, Myle Ott, Jingfei Du and Veselin Stoyanov . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 146", | |
| "links": null | |
| }, | |
| "BIBREF3": { | |
| "ref_id": "b3", | |
| "title": "Assessment of DistilBERT performance on Named Entity Recognition task for the detection of Protected Health Information and medical concepts Macarious Abadeer", | |
| "authors": [], | |
| "year": null, | |
| "venue": "", | |
| "volume": "", | |
| "issue": "", | |
| "pages": "", | |
| "other_ids": {}, | |
| "num": null, | |
| "urls": [], | |
| "raw_text": "Assessment of DistilBERT performance on Named Entity Recognition task for the detection of Protected Health Information and medical concepts Macarious Abadeer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 158", | |
| "links": null | |
| }, | |
| "BIBREF4": { | |
| "ref_id": "b4", | |
| "title": "Distinguishing between Dementia with Lewy bodies (DLB) and Alzheimer's Disease (AD) using Mental Health Records: a Classification Approach Zixu Wang, Julia Ive", | |
| "authors": [ | |
| { | |
| "first": "Sinead", | |
| "middle": [], | |
| "last": "Moylett", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "Christoph", | |
| "middle": [], | |
| "last": "Mueller", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "Rudolf", | |
| "middle": [], | |
| "last": "Cardinal", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "Sumithra", | |
| "middle": [], | |
| "last": "Velupillai", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "O'", | |
| "middle": [], | |
| "last": "John", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "Robert", | |
| "middle": [], | |
| "last": "Brien", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": ".", | |
| "middle": [ | |
| "." | |
| ], | |
| "last": "Stewart", | |
| "suffix": "" | |
| } | |
| ], | |
| "year": null, | |
| "venue": "", | |
| "volume": "", | |
| "issue": "", | |
| "pages": "", | |
| "other_ids": {}, | |
| "num": null, | |
| "urls": [], | |
| "raw_text": "Distinguishing between Dementia with Lewy bodies (DLB) and Alzheimer's Disease (AD) using Mental Health Records: a Classification Approach Zixu Wang, Julia Ive, Sinead Moylett, Christoph Mueller, Rudolf Cardinal, Sumithra Velupillai, John O'Brien and Robert Stewart . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 168", | |
| "links": null | |
| }, | |
| "BIBREF5": { | |
| "ref_id": "b5", | |
| "title": "Weakly Supervised Medication Regimen Extraction from Medical Conversations Dhruvesh Patel, Sandeep Konam and Sai Prabhakar", | |
| "authors": [], | |
| "year": null, | |
| "venue": "", | |
| "volume": "", | |
| "issue": "", | |
| "pages": "", | |
| "other_ids": {}, | |
| "num": null, | |
| "urls": [], | |
| "raw_text": "Weakly Supervised Medication Regimen Extraction from Medical Conversations Dhruvesh Patel, Sandeep Konam and Sai Prabhakar . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 178", | |
| "links": null | |
| }, | |
| "BIBREF6": { | |
| "ref_id": "b6", | |
| "title": "Extracting Relations between Radiotherapy Treatment Details Danielle", | |
| "authors": [ | |
| { | |
| "first": "Timothy", | |
| "middle": [], | |
| "last": "Bitterman", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "David", | |
| "middle": [], | |
| "last": "Miller", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "Chen", | |
| "middle": [], | |
| "last": "Harris", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "Sean", | |
| "middle": [], | |
| "last": "Lin", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "Jeremy", | |
| "middle": [], | |
| "last": "Finan", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "Raymond", | |
| "middle": [], | |
| "last": "Warner", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "Guergana", | |
| "middle": [], | |
| "last": "Mak", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": ".", | |
| "middle": [ | |
| "." | |
| ], | |
| "last": "Savova", | |
| "suffix": "" | |
| } | |
| ], | |
| "year": null, | |
| "venue": "", | |
| "volume": "", | |
| "issue": "", | |
| "pages": "", | |
| "other_ids": {}, | |
| "num": null, | |
| "urls": [], | |
| "raw_text": "Extracting Relations between Radiotherapy Treatment Details Danielle Bitterman, Timothy Miller, David Harris, Chen Lin, Sean Finan, Jeremy Warner, Raymond Mak and Guergana Savova . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 194", | |
| "links": null | |
| }, | |
| "BIBREF7": { | |
| "ref_id": "b7", | |
| "title": "PHICON: Improving Generalization of Clinical Text De-identification Models via Data Augmentation Xiang Yue and", | |
| "authors": [ | |
| { | |
| "first": "Yan-Jie", | |
| "middle": [], | |
| "last": "Lin", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "Hong-Jie", | |
| "middle": [], | |
| "last": "Dai", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "You-Chen", | |
| "middle": [], | |
| "last": "Zhang", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "Chung-Yang", | |
| "middle": [], | |
| "last": "Wu", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "Yu-Cheng", | |
| "middle": [], | |
| "last": "Chang", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "Pin-Jou", | |
| "middle": [], | |
| "last": "Lu", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "Chih-Jen", | |
| "middle": [], | |
| "last": "Huang", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "Yu-Tsang", | |
| "middle": [], | |
| "last": "Wang", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "Hui-Min", | |
| "middle": [], | |
| "last": "Hsieh", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "Kun-San", | |
| "middle": [], | |
| "last": "Chao", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "Tsang-Wu", | |
| "middle": [], | |
| "last": "Liu", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "I-Shou", | |
| "middle": [], | |
| "last": "Chang", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "Yi-Hsin Connie", | |
| "middle": [], | |
| "last": "Yang", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "Ti-Hao", | |
| "middle": [], | |
| "last": "Wang", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "Ko-Jiunn", | |
| "middle": [], | |
| "last": "Liu", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "Li-Tzong", | |
| "middle": [], | |
| "last": "Chen", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "Sheau-Fang", | |
| "middle": [ | |
| ". . . . ." | |
| ], | |
| "last": "Yang", | |
| "suffix": "" | |
| } | |
| ], | |
| "year": null, | |
| "venue": "Cancer Registry Information Extraction via Transfer Learning", | |
| "volume": "", | |
| "issue": "", | |
| "pages": "", | |
| "other_ids": {}, | |
| "num": null, | |
| "urls": [], | |
| "raw_text": "Cancer Registry Information Extraction via Transfer Learning Yan-Jie Lin, Hong-Jie Dai, You-Chen Zhang, Chung-Yang Wu, Yu-Cheng Chang, Pin-Jou Lu, Chih-Jen Huang, Yu-Tsang Wang, Hui-Min Hsieh, Kun-San Chao, Tsang-Wu Liu, I-Shou Chang, Yi- Hsin Connie Yang, Ti-Hao Wang, Ko-Jiunn Liu, Li-Tzong Chen and Sheau-Fang Yang . . . . . . . . . . . . 201 PHICON: Improving Generalization of Clinical Text De-identification Models via Data Augmentation Xiang Yue and Shuang Zhou . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 209", | |
| "links": null | |
| }, | |
| "BIBREF8": { | |
| "ref_id": "b8", | |
| "title": "Where's the Question? A Multi-channel Deep Convolutional Neural Network for Question Identification in Textual Data George Michalopoulos", | |
| "authors": [ | |
| { | |
| "first": "Helen", | |
| "middle": [], | |
| "last": "Chen", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "Alexander", | |
| "middle": [], | |
| "last": "Wong", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": ".", | |
| "middle": [ | |
| "." | |
| ], | |
| "last": "", | |
| "suffix": "" | |
| } | |
| ], | |
| "year": null, | |
| "venue": "", | |
| "volume": "", | |
| "issue": "", | |
| "pages": "", | |
| "other_ids": {}, | |
| "num": null, | |
| "urls": [], | |
| "raw_text": "Where's the Question? A Multi-channel Deep Convolutional Neural Network for Question Identification in Textual Data George Michalopoulos, Helen Chen and Alexander Wong . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 215", | |
| "links": null | |
| }, | |
| "BIBREF9": { | |
| "ref_id": "b9", | |
| "title": "Learning from Unlabelled Data for Clinical Semantic Textual Similarity Yuxia Wang, Karin Verspoor and Timothy Baldwin", | |
| "authors": [], | |
| "year": null, | |
| "venue": "", | |
| "volume": "", | |
| "issue": "", | |
| "pages": "", | |
| "other_ids": {}, | |
| "num": null, | |
| "urls": [], | |
| "raw_text": "Learning from Unlabelled Data for Clinical Semantic Textual Similarity Yuxia Wang, Karin Verspoor and Timothy Baldwin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 227", | |
| "links": null | |
| }, | |
| "BIBREF10": { | |
| "ref_id": "b10", | |
| "title": "Joint Learning with Pre-trained Transformer on Named Entity Recognition and Relation Extraction Tasks for Clinical Analytics", | |
| "authors": [ | |
| { | |
| "first": "Miao", | |
| "middle": [], | |
| "last": "Chen", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "Ganhui", | |
| "middle": [], | |
| "last": "Lan", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "Fang", | |
| "middle": [], | |
| "last": "Du", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": ".", | |
| "middle": [ | |
| "." | |
| ], | |
| "last": "Victor Lobanov", | |
| "suffix": "" | |
| } | |
| ], | |
| "year": null, | |
| "venue": "", | |
| "volume": "", | |
| "issue": "", | |
| "pages": "", | |
| "other_ids": {}, | |
| "num": null, | |
| "urls": [], | |
| "raw_text": "Joint Learning with Pre-trained Transformer on Named Entity Recognition and Relation Extraction Tasks for Clinical Analytics Miao Chen, Ganhui Lan, Fang Du and Victor Lobanov . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 234", | |
| "links": null | |
| }, | |
| "BIBREF11": { | |
| "ref_id": "b11", | |
| "title": "Extracting Semantic Aspects for Structured Representation of Clinical Trial Eligibility Criteria Tirthankar Dasgupta, Ishani Mondal, abir naskar and Lipika Dey", | |
| "authors": [], | |
| "year": null, | |
| "venue": "", | |
| "volume": "", | |
| "issue": "", | |
| "pages": "", | |
| "other_ids": {}, | |
| "num": null, | |
| "urls": [], | |
| "raw_text": "Extracting Semantic Aspects for Structured Representation of Clinical Trial Eligibility Criteria Tirthankar Dasgupta, Ishani Mondal, abir naskar and Lipika Dey . . . . . . . . . . . . . . . . . . . . . . . . . . . 243", | |
| "links": null | |
| }, | |
| "BIBREF13": { | |
| "ref_id": "b13", | |
| "title": "Utilizing Multimodal Feature Consistency to Detect Adversarial Examples on Clinical Summaries Wenjie Wang", | |
| "authors": [ | |
| { | |
| "first": "Youngja", | |
| "middle": [], | |
| "last": "Park", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "Taesung", | |
| "middle": [], | |
| "last": "Lee", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "Ian", | |
| "middle": [], | |
| "last": "Molloy", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "Pengfei", | |
| "middle": [], | |
| "last": "Tang", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "Li", | |
| "middle": [ | |
| ". . . . ." | |
| ], | |
| "last": "Xiong", | |
| "suffix": "" | |
| } | |
| ], | |
| "year": null, | |
| "venue": "", | |
| "volume": "", | |
| "issue": "", | |
| "pages": "", | |
| "other_ids": {}, | |
| "num": null, | |
| "urls": [], | |
| "raw_text": "Utilizing Multimodal Feature Consistency to Detect Adversarial Examples on Clinical Summaries Wenjie Wang, Youngja Park, Taesung Lee, Ian Molloy, Pengfei Tang and Li Xiong . . . . . . . . . . . 259", | |
| "links": null | |
| }, | |
| "BIBREF14": { | |
| "ref_id": "b14", | |
| "title": ":46 How You Ask Matters: The Effect of Paraphrastic Questions to BERT Performance on a Clinical SQuAD Dataset Sungrim (Riea) Moon and Jungwei Fan 11:46-11:47 Relative and Incomplete Time Expression Anchoring for Clinical Text Louise Dupuis, Nicol Bergou, Hegler Tissot and Sumithra Velupillai 11:47-11:48 MeDAL: Medical Abbreviation Disambiguation Dataset for Natural Language Understanding Pretraining Zhi Wen", | |
| "authors": [ | |
| { | |
| "first": "Mei-Hua", | |
| "middle": [], | |
| "last": "Hall", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "Timothy", | |
| "middle": [], | |
| "last": "Miller ; Narayanan", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "Kaivalya", | |
| "middle": [], | |
| "last": "Mannam", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "P", | |
| "middle": [], | |
| "last": "Sreeranga", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "", | |
| "middle": [], | |
| "last": "Rajan", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": ";", | |
| "middle": [], | |
| "last": "Venkat", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "Jo\u00e3o", | |
| "middle": [], | |
| "last": "Schneider", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "Julien", | |
| "middle": [], | |
| "last": "Vitor Andrioli De Souza", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "Lucas", | |
| "middle": [ | |
| "Emanuel" | |
| ], | |
| "last": "Knafou", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "Jenny", | |
| "middle": [], | |
| "last": "Silva E Oliveira", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "Yohan", | |
| "middle": [], | |
| "last": "Copara", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "Lucas", | |
| "middle": [], | |
| "last": "Bonescki Gumiel", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "Emerson", | |
| "middle": [ | |
| "Cabrera" | |
| ], | |
| "last": "Ferro Antunes De Oliveira", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "Douglas", | |
| "middle": [], | |
| "last": "Paraiso", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "Cl\u00e1udia Maria", | |
| "middle": [], | |
| "last": "Teodoro", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "H", | |
| "middle": [], | |
| "last": "Cabral ; P\u00e5l", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "Fredrik", | |
| "middle": [ | |
| "A" | |
| ], | |
| "last": "Brekke", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "Tore", | |
| "middle": [], | |
| "last": "Dahl", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "Haldor", | |
| "middle": [], | |
| "last": "Gundersen", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "", | |
| "middle": [], | |
| "last": "Husby ; Abhishek", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "Sitong", | |
| "middle": [], | |
| "last": "Singh", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "Edward", | |
| "middle": [], | |
| "last": "Chen", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "Chih-Ying", | |
| "middle": [], | |
| "last": "Moseley", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "Naomi", | |
| "middle": [], | |
| "last": "Deng", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "Charolotta", | |
| "middle": [], | |
| "last": "George", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "", | |
| "middle": [], | |
| "last": "Lindvall Xii ; Sungwon", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "Daniel", | |
| "middle": [ | |
| "C" | |
| ], | |
| "last": "Lee", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "Thomas", | |
| "middle": [], | |
| "last": "Elton", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "Yu-Xing", | |
| "middle": [], | |
| "last": "Shen", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "Qingyu", | |
| "middle": [], | |
| "last": "Tang", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "Shuai", | |
| "middle": [], | |
| "last": "Chen", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "Yingying", | |
| "middle": [], | |
| "last": "Wang", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "Ronald", | |
| "middle": [], | |
| "last": "Zhu", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "Zhiyong", | |
| "middle": [], | |
| "last": "Summers", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "; Timothy", | |
| "middle": [], | |
| "last": "Lu", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "David", | |
| "middle": [], | |
| "last": "Miller", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "Chen", | |
| "middle": [], | |
| "last": "Harris", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "Sean", | |
| "middle": [], | |
| "last": "Lin", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "Jeremy", | |
| "middle": [], | |
| "last": "Finan", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "Raymond", | |
| "middle": [], | |
| "last": "Warner", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "Guergana", | |
| "middle": [], | |
| "last": "Mak", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "; Jiazhao", | |
| "middle": [], | |
| "last": "Savova", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "Corey", | |
| "middle": [], | |
| "last": "Li", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "Xinyan", | |
| "middle": [], | |
| "last": "Lester", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "Yuting", | |
| "middle": [], | |
| "last": "Zhao", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "Yun", | |
| "middle": [], | |
| "last": "Ding", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "", | |
| "middle": [], | |
| "last": "Jiang", | |
| "suffix": "" | |
| } | |
| ], | |
| "year": 2020, | |
| "venue": "51 Assessment of DistilBERT performance on Named Entity Recognition task for the detection of Protected Health Information and medical concepts Macarious Abadeer", | |
| "volume": "10", | |
| "issue": "", | |
| "pages": "20--36", | |
| "other_ids": {}, | |
| "num": null, | |
| "urls": [], | |
| "raw_text": "19 Nov 2020 (continued) 10:40-10:50 Coffee Break 10:50-11:40 Oral Session 2 10:50-10:55 Incorporating Risk Factor Embeddings in Pre-trained Transformers Improves Sen- timent Prediction in Psychiatric Discharge Summaries Xiyu Ding, Mei-Hua Hall and Timothy Miller 10:55-11:05 Information Extraction from Swedish Medical Prescriptions with Sig-Transformer Encoder John Pougu\u00e9 Biyong, Bo Wang, Terry Lyons and Alejo Nevado-Holgado 11:05-11:15 Evaluation of Transfer Learning for Adverse Drug Event (ADE) and Medication Entity Extraction Sankaran Narayanan, Kaivalya Mannam, Sreeranga P Rajan and P Venkat Rangan 11:15-11:25 BioBERTpt -A Portuguese Neural Language Model for Clinical Named Entity Recognition Elisa Terumi Rubel Schneider, Jo\u00e3o Vitor Andrioli de Souza, Julien Knafou, Lucas Emanuel Silva e Oliveira, Jenny Copara, Yohan Bonescki Gumiel, Lucas Ferro An- tunes de Oliveira, Emerson Cabrera Paraiso, Douglas Teodoro and Cl\u00e1udia Maria Cabral Moro Barra 11:25-11:40 Oral Session 2: Q&A 11:40-12:00 Poster Teasers 11:40-11:41 Dilated Convolutional Attention Network for Medical Code Assignment from Clini- cal Text Shaoxiong Ji, Erik Cambria and Pekka Marttinen 11:41-11:42 Classification of Syncope Cases in Norwegian Medical Records Ildiko Pilan, P\u00e5l H. Brekke, Fredrik A. Dahl, Tore Gundersen, Haldor Husby, \u00d8ys- tein Nytr\u00f8 and Lilja \u00d8vrelid 11:42-11:43 Comparison of Machine Learning Methods for Multi-label Classification of Nursing Education and Licensure Exam Questions John Langton, Krishna Srihasam and Junlin Jiang 11:43-11:44 Clinical XLNet: Modeling Sequential Clinical Notes and Predicting Prolonged Me- chanical Ventilation Kexin Huang, Abhishek Singh, Sitong Chen, Edward Moseley, Chih-Ying Deng, Naomi George and Charolotta Lindvall xii 19 Nov 2020 (continued) 11:44-11:45 Automatic recognition of abdominal lymph nodes from clinical text Yifan Peng, Sungwon Lee, Daniel C. Elton, Thomas Shen, Yu-xing Tang, Qingyu Chen, Shuai Wang, Yingying Zhu, Ronald Summers and Zhiyong Lu 11:45-11:46 How You Ask Matters: The Effect of Paraphrastic Questions to BERT Performance on a Clinical SQuAD Dataset Sungrim (Riea) Moon and Jungwei Fan 11:46-11:47 Relative and Incomplete Time Expression Anchoring for Clinical Text Louise Dupuis, Nicol Bergou, Hegler Tissot and Sumithra Velupillai 11:47-11:48 MeDAL: Medical Abbreviation Disambiguation Dataset for Natural Language Un- derstanding Pretraining Zhi Wen, Xing Han Lu and Siva Reddy 11:48-11:49 Knowledge Grounded Conversational Symptom Detection with Graph Memory Net- works Hongyin Luo, Shang-Wen Li and James Glass 11:49-11:50 Pretrained Language Models for Biomedical and Clinical Tasks: Understanding and Extending the State-of-the-Art Patrick Lewis, Myle Ott, Jingfei Du and Veselin Stoyanov 11:50-11:51 Assessment of DistilBERT performance on Named Entity Recognition task for the detection of Protected Health Information and medical concepts Macarious Abadeer 11:51-11:52 Distinguishing between Dementia with Lewy bodies (DLB) and Alzheimer's Disease (AD) using Mental Health Records: a Classification Approach Zixu Wang, Julia Ive, Sinead Moylett, Christoph Mueller, Rudolf Cardinal, Sum- ithra Velupillai, John O'Brien and Robert Stewart 11:52-11:53 Weakly Supervised Medication Regimen Extraction from Medical Conversations Dhruvesh Patel, Sandeep Konam and Sai Prabhakar 11:53-11:54 Extracting Relations between Radiotherapy Treatment Details Danielle Bitterman, Timothy Miller, David Harris, Chen Lin, Sean Finan, Jeremy Warner, Raymond Mak and Guergana Savova 11:54-11:55 Cancer Registry Information Extraction via Transfer Learning Yan-Jie Lin, Hong-Jie Dai, You-Chen Zhang, Chung-Yang Wu, Yu-Cheng Chang, Pin-Jou Lu, Chih-Jen Huang, Yu-Tsang Wang, Hui-Min Hsieh, Kun-San Chao, Tsang-Wu Liu, I-Shou Chang, Yi-Hsin Connie Yang, Ti-Hao Wang, Ko-Jiunn Liu, Li-Tzong Chen and Sheau-Fang Yang 11:55-11:56 PHICON: Improving Generalization of Clinical Text De-identification Models via Data Augmentation Xiang Yue and Shuang Zhou xiii 19 Nov 2020 (continued) 11:56-11:57 Where's the Question? A Multi-channel Deep Convolutional Neural Network for Question Identification in Textual Data George Michalopoulos, Helen Chen and Alexander Wong 11:57-11:58 Learning from Unlabelled Data for Clinical Semantic Textual Similarity Yuxia Wang, Karin Verspoor and Timothy Baldwin 11:58-11:59 Joint Learning with Pre-trained Transformer on Named Entity Recognition and Re- lation Extraction Tasks for Clinical Analytics Miao Chen, Ganhui Lan, Fang Du and Victor Lobanov 12:00-13:20 Poster Session & Lunch 13:20-14:10 Oral Session 3 13:20-13:25 Extracting Semantic Aspects for Structured Representation of Clinical Trial Eligi- bility Criteria Tirthankar Dasgupta, Ishani Mondal, abir naskar and Lipika Dey 13:25-13:35 An Ensemble Approach to Automatic Structuring of Radiology Reports Morteza Pourreza Shahri, Amir Tahmasebi, Bingyang Ye, Henghui Zhu, Javed Aslam and Timothy Ferris 13:35-13:45 Utilizing Multimodal Feature Consistency to Detect Adversarial Examples on Clin- ical Summaries Wenjie Wang, Youngja Park, Taesung Lee, Ian Molloy, Pengfei Tang and Li Xiong 13:45-13:55 Advancing Seq2seq with Joint Paraphrase Learning So Yeon Min, Preethi Raghavan and Peter Szolovits 13:55-14:10 Oral Session 3: Q&A xiv 19 Nov 2020 (continued) 14:10-14:55 EMNLP Findings Session 1 14:10-14:15 Learning to Generate Clinically Coherent Chest X-Ray Reports Justin Lovelace, Bobak Mortazavi 14:15-14:20 Learning Visual-Semantic Embeddings for Reporting Abnormal Findings on Chest X-rays Jianmo Ni, Chun-Nan Hsu, Amilcare Gentili, Julian McAuley 14:20-14:30 Characterizing the Value of Information in Medical Notes Chao-Chun Hsu, Shantanu Karnwal, Sendhil Mullainathan, Ziad Obermeyer, Chen- hao Tan 14:30-14:40 PharmMT: A Neural Machine Translation Approach to Simplify Prescription Direc- tions Jiazhao Li, Corey Lester, Xinyan Zhao, Yuting Ding, Yun Jiang, V.G.Vinod Vydis- waran 14:40-14:55 EMNLP Findings Session 1: Q&A 14:55-15:05 Coffee Break 15:05-15:50 EMNLP Findings Session 2 15:05-15:15 A Dual-Attention Network for Joint Named Entity Recognition and Sentence Clas- sification of Adverse Drug Events Susmitha Wunnava, Xiao Qin, Tabassum Kakar, Xiangnan Kong, Elke A. Runden- steiner 15:15-15:25 Dr. Summarize: Global Summarization of Medical Dialogue by Exploiting Local Structures Anirudh Joshi, Namit Katariya, Xavier Amatriain, Anitha Kannan 15:25-15:35 Generating Accurate Electronic Health Assessment from Medical Graph Zhichao Yang, Hong Yu 15:35-15:50 EMNLP Findings Session 2: Q&A xv 19 Nov 2020 (continued) 15:50-16:35 Best Paper Session 15:50-16:00 On the diminishing return of labeling clinical reports Jean-Baptiste Lamare, Oloruntobiloba Olatunji and Li Yao 16:00-16:10 The Chilean Waiting List Corpus: a new resource for clinical Named Entity Recog- nition in Spanish Pablo B\u00e1ez, Fabi\u00e1n Villena, Mat\u00edas Rojas, Manuel Dur\u00e1n and Jocelyn Dunstan 16:10-16:20 Analyzing Text Specific vs Blackbox Fairness Algorithms in Multimodal Clinical NLP John Chen, Ian Berlot-Attwell, Xindi Wang, Safwan Hossain and Frank Rudzicz 16:20-16:35 Best Paper Session: Q&A 16:35-16:50 Concluding Session", | |
| "links": null | |
| } | |
| }, | |
| "ref_entries": {} | |
| } | |
| } |