Call for Papers

Clinical text is growing rapidly as electronic health records become pervasive. Much of the information recorded in a clinical encounter is located exclusively in provider narrative notes, which makes them indispensable for supplementing structured clinical data in order to better understand patient state and care provided. The methods and tools developed for the clinical domain have historically lagged behind the scientific advances in the general-domain NLP. Despite the substantial recent strides in clinical NLP, a substantial gap remains. The goal of this workshop is to address this gap by establishing a regular event in CL conferences that brings together researchers interested in developing state-of-the-art methods for the clinical domain. The focus is on improving NLP technology to enable clinical applications, and specifically, information extraction and modeling of narrative provider notes from electronic health records, patient encounter transcripts, and other clinical narratives.

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 non-standard 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.

We invite high-quality original submissions that develop methods to address the above challenges to NLP in the clinical domain. We are interested in work that specifically focuses on advancing the state-of-the-art in clinical NLP, rather than merely applies existing NLP systems to downstream clinical problems (such as outcome prediction or clinical cohort selection). The submissions may include initial results from promising new methods that may spark interest from other members of the Clinical NLP community and lead to collaborative work. The following is a list of topics of interest for this workshop:

• Modeling clinical text in standard NLP tasks (tagging, chunking, parsing, entity identification, relation extraction, coreference, summarization, etc.)
• De-identification and other handling of protected health information
• Structure of clinical documents (e.g., section identification)
• Information extraction from clinical text
• Integration of structured and textual data for clinical tasks
• Domain adaptation techniques for clinical data
• Medical terminologies and ontologies
• Annotation schemes and annotation methodology for clinical data
• Evaluation techniques for the clinical domain

Submissions

All submissions must be in PDF format and should follow EMNLP 2020 style guidelines:
https://2020.emnlp.org/call-for-papers

Submissions may have a maximum length of eight (8) pages for long papers and four (4) pages for short papers, with unlimited pages for references and appendices. Both long and short papers will undergo rigorous review. All submissions should be anonymized, and should not include authors' names or any other identifying information. Please submit at the following site:
https://www.softconf.com/emnlp2020/clinicalnlp/

Supplementary Material: Clinical NLP 2020 does not allow any separate supplementary material to be uploaded. Additional textual material that supports the paper may be placed in an appendix. (Appendices do not count against page limits, but reviewers will be instructed that reviewing appendices is optional.) If the work includes software or data, it may not be submitted with the paper, though anonymized links to the software or data may be included in the paper text. (Make sure you do not include, for example, links to a GitHub repository that includes author names or institutions.) For accepted papers, the camera-ready submissions may include non-anonymized links.

Multiple Submission Policy: Clinical NLP 2020 will not consider any paper that is under review in a journal, conference, or workshop at the time of submission, and submitted papers must not be submitted elsewhere during the Clinical NLP 2020 review period. This policy covers all refereed and archival conferences and workshops (e.g., COLING, NeurIPS, ACL workshops). For example, a paper under review at an ACL workshop cannot be dual-submitted to Clinical NLP 2020. The only exception is that a paper can be dual-submitted to both EMNLP 2020 and Clinical NLP 2020, but the EMNLP 2020 submission ID must be included in the Clinical NLP submission form so that the EMNLP reviews can be transferred to the Clinical NLP reviewers.

Important Dates

Submissions due (both short and long)	Saturday	August 15, 2020
Retraction of papers accepted to EMNLP	Tuesday	September 15, 2020
Notification of acceptance	Tuesday	September 29, 2020
Camera-ready papers due	Saturday	October 10, 2020
Workshop	Thursday	Nov 19, 2020

Workshop Organizers

• Anna Rumshisky (UMass Lowell)
• Kirk Roberts (University of Texas Health Science Center at Houston)
• Steven Bethard (University of Arizona)
• Tristan Naumann (Microsoft Research)

Program Committee

• Sabine Bergler (Concordia University)
• Parminder Bhatia (Amazon)
• Vivek Datla (Philips Research North America)
• Dmitriy Dligach (Loyola University)
• Jungwei Fan (Mayo Clinic)
• Sadid Hasan (CVS Health)
• Lynette Hirschman (The MITRE Corporation)
• Yoshinobu Kano (Shizuoka University)
• Timothy Miller (Boston Children’s Hospital)
• Hoifung Poon (Microsoft Research)
• Chaitanya Shivade (Amazon)
• Sumithra Velupillai (KTH Royal Institute of Technology)
• Karin Verspoor (The University of Melbourne)
• Byron Wallace (Northeastern University)
• Ben Wellner (The MITRE Corporation)
• Stephen Wu (University of Texas Health Science Center at Houston)