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.
Relevant topics for the workshop include, but are not limited to:
- Modeling clinical text in standard NLP tasks (tagging, chunking, parsing, entity identification, entity linking/normalization, 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 and transfer learning techniques for clinical data - Generation of clinical notes: summarization, image-to-text, generation of notes from clinical conversations, etc. - Annotation schemes and annotation methodology for clinical data - Evaluation techniques for the clinical domain - Bias and fairness in clinical text
In 2023, Clinical NLP will encourage submissions from the following special tracks:
- Clinical NLP in languages other than English - Clinical NLP in low-resource settings - Clinical NLP for clinical conversations (e.g., doctor-patient)
The 5th Clinical NLP Workshop will be co-located with ACL 2023 https://2023.aclweb.org/ in Toronto, Canada - July 13 or 14, 2023. Joint Track with MWE
Clinical NLP 2023 is also co-organizing a special track with the 19th Workshop on Multiword Expressions (MWE 2023) https://multiword.org/mwe2023/. The goal is to foster future synergies that could address scientific challenges in the creation of resources, models and applications to deal with multiword expressions and related phenomena in the specialised domain of Clinical NLP. Submissions describing research on multi-word expressions in the specialized domain of Clinical NLP, especially introducing new datasets or new tools and resources, are welcome.
Note that submissions to this track must be submitted to MWE, not Clinical NLP by their earlier submission deadline, 20 Feb 2023. Please visit the MWE 2023 website https://multiword.org/mwe2023/ for more details. Submissions accepted to this “Multi-word expressions in Clinical NLP” special track will have the opportunity to present their work first at MWE 2023 at EACL and then also at Clinical NLP 2023 at ACL. Shared Task
Clinical NLP 2023 is hosting the MEDIQA-Chat Shared Tasks https://sites.google.com/view/mediqa2023/clinicalnlp-mediqa-chat-2023 on doctor-patient conversations, which focuses on the following tasks:
1. Dialogue2Note Summarization: Given a conversation between a doctor and patient, participants are tasked with producing a clinical note summarizing the conversation with one or multiple note sections (e.g. Assessment, Past Medical History, Past Surgical History). 2. Note2Dialogue Generation: Given a clinical note, participants are tasked with generating a synthetic doctor-patient conversation related to the information described in the clinical note section(s).
Please visit the shared task website https://sites.google.com/view/mediqa2023/clinicalnlp-mediqa-chat-2023 to register to participate and for additional information about the shared tasks. Submissions
Submissions may have a maximum length of eight (8) pages for long papers and four (4) pages for short papers and shared task participant papers, with unlimited pages for references and appendices. All submissions must be made through OpenReview https://openreview.net/ and follow ACL formatting guidelines https://acl-org.github.io/ACLPUB/formatting.html.
The OpenReview submission site can be found here: OpenReview-ClinicalNLP https://openreview.net/group?id=aclweb.org/ACL/2023/Workshop/Clinical_NLP
We encourage submissions of papers submitted to but not accepted by EACL 2023 https://2023.eacl.org/, ACL 2023 https://2023.aclweb.org/, or ACL Rolling Review https://aclrollingreview.org/, as long as the topics are relevant to Clinical NLP. Important Dates
All deadlines are 11:59PM UTC-12:00 (anywhere on Earth https://www.timeanddate.com/time/zones/aoe) EventDate Shared task registration opens Tuesday, January 10, 2023 Shared task release of training and validation sets Friday, February 10, 2023 Shared task release of the test sets Wednesday, March 15, 2023 Shared task run submission deadline Friday, March 17, 2023 Shared task release of official results Friday, March 31, 2023 Submission deadline (both general and shared task) Tuesday, May 2, 2023 Notification of acceptance Monday, May 22, 2023 Final versions of papers due Tuesday, June 6, 2023 Pre-recorded video due Monday, June 12, 2023 Workshop Thursday or Friday, July 13 or 14, 2023Workshop Organizers
- Anna Rumshisky (UMass Lowell) - Asma Ben Abacha (Microsoft) - Kirk Roberts (University of Texas Health Science Center at Houston) - Steven Bethard (University of Arizona) - Tristan Naumann (Microsoft Research)
For inquiries, please contact: clinical-nlp-workshop-organizers@googlegroups.com.