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NLP4MC 2021 : The Second Workshop on NLP for Medical Conversations


When Jun 6, 2021 - Jun 6, 2021
Where Virtual/Online
Submission Deadline Mar 15, 2021
Notification Due Apr 15, 2021
Final Version Due Apr 21, 2021
Categories    NLP

Call For Papers

We are pleased to announce the second workshop on NLP for Medical Conversations to be held online on June 6th 2021 in conjunction with NAACL-2021. We invite the submission of papers on original and unpublished research in this upcoming area of interest.

**About the Workshop**

The goal of this workshop is to bring together NLP researchers and medical practitioners, along with experts in machine learning, to discuss the current state-of-the-art approaches, to share their insights and discuss challenges. This is critical in order to bridge existing gaps between research and real-world product deployments, this will further shed light on future directions. “NLP for Medical Conversations” will be a one-day workshop including keynotes, spotlight talks, posters, and panel sessions. In keynote talks, senior technical leaders from industry and academia will share insights on the latest development of the field. The panel discussion will focus on the challenges, common framework for evaluating models across sites and future directions of conversational AI research in the medical domain, bridging the gap in research and industrial practice, as well as audience-suggested topics.

**Important Dates**

- Paper submission deadline: Monday, March 15th, 2021 11:59 PM UTC-12h.
- Acceptance notification: Thursday, April 15th, 2021
- Camera-ready deadline: Wednesday, April 21st, 2021
- NAACL conference dates: June 6th - June 11th, 2021
- Workshop: June 6th, 2021

**Submission Instructions**

Two types of submissions are invited: full papers and short papers. Full papers should not exceed eight (8) pages of text, plus unlimited references. Final versions of full papers will be given one additional page of content (up to 9 pages) so that reviewers' comments can be taken into account. Short papers may consist of up to four (4) pages of content, plus unlimited references. Upon acceptance, short papers will still be given up to five (5) content pages in the proceedings.

**Cross Submissions**

In addition to previously unpublished work, we invite papers on relevant topics which have been submitted to alternative venues (such as other NLP or ML conferences). Please follow double-submission policy from ACL. Accepted cross-submissions will be presented as posters, with an indication of the original venue. Selection of cross-submissions will be determined solely by the organizing committee.

**Areas of Interest**

The active areas of research include, but are not limited to:
- Medical conversation summarization
- Entity recognition in Medical conversations
- Extraction of relations and events in Medical conversations
- Entity Linking with medical ontologies
- Topic Models for medical conversations
- Dissemination of resources for Medical conversation analysis
- Strategies to evaluate automated understanding of Medical conversations
- Resource sharing or dataset release
- Handling Multimodal clinical data
- Infrastructures for Clinical Decision Making
- Survey and Trends in Medical Conversational AI
- Language Understanding (NLU / SLU)
- Language Generation
- Medical Conversational AI Deployment
- Dialogue State Tracking
- Dialogue Data Collection / Datasets
- End-to-End Dialogue Modeling
- Slot-based Conversational AI
- Retrieval-based Conversational AI
- Generative Conversational AI
- Multimodal Dialogues
- Contextual Modeling
- Coreference Resolution
- Semantic Representation
- Dialogue Representation Learning
- Emergence of Communication
- Conversational Recommendations
- Patient modeling for Conversational AI
- Learning from user feedback

**Author responsibility**

We encourage submitting interesting ideas, these ideas can also be preliminary and unpublished work. The goal is to trigger discussion even when the idea is not ready for publication. Reviewing will be blind, so please refrain from including any names, affiliations or obvious statements in the paper, such as, “in our previous paper \cite{John:19}”.

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