Natural Language Processing (NLP) for clinical and biomedical narratives has received growing attention over the past decade. As these efforts grew, so has the need for broader community engagement and resource sharing. As a result, many NLP-ready data sources and software have been developed and shared. These efforts have provided significant learning opportunities for new comers to the field and have supported advancement of the state of the art. In its support of these goals, the AMIA NLP working group pre-symposium continues the tradition since its inception in 2012 to provide a unique platform for close interactions among students, scholars, and industry professionals who are interested in clinical NLP for data and resource sharing. This year’s proposed event will consist of three sections: 1) a graduate student consortium, where students can present their work and get feedback from faculty; 2) a NLP community challenges and workshops session, that will invite organizers and participants of NLP shared task challenges and workshops in the clinical and biomedical domain to present the major lessons learned from the most recent shared tasks and workshops, highlighting the newly available corpora for NLP research as well as the state of the art solutions to various NLP tasks; and 3) System demos session, where researchers will demo their existing systems and disseminate their software.
Learning Objective: After participating in this session, attendees will be better able to:
1. Build on expert feedback on issues related to their research,
2. Identify the latest advancements in the field,
3. Familiarize themselves with existing and available clinical and biomedical NLP tools, resources, and challenges.
Ozlem Uzuner (Presenter)
George Mason University
Meliha Yetisgen (Presenter)
University of Washington
Hongfang Liu (Presenter)