Abstract: The application of Natural Language Processing (NLP) methods and resources to clinical and biomedical text has received growing attention over the past years, but progress has been limited by difficulties to access shared tools and resources, partially caused by patient privacy and data confidentiality constraints. Efforts to increase sharing and interoperability of the few existing resources are needed to facilitate the progress observed in the general NLP domain. To answer this need, 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. The event will consist of three sections: 1) a graduate student consortium, where students can present their work and get feedback from experienced researchers in the field; 2) a highlight session, where significant NLP articles in clinical and biomedical domains will be presented followed by a panel discussion; and 3) a ‘codeathon’ of NLP tools, where user developers of NLP tools will interact with tool developers to implement tools on practical NLP tasks in groups.

Learning Objective 1: Implement constructive feedback on their graduate research efforts
Discover and understand existing and available clinical and biomedical NLP tools and resources as well as the recent advancement in the field
Users will gain a hands on experience of using the tools with expert guidance
Providers (tool developers) will have a better understanding of the usability and robustness of their tools and areas of improvement.


Hongfang Liu (Presenter)
Mayo Clinic

Rong Xu, Case Western Reserve University
Stephane Meystre, Medical University of South Carolina
Sivaram Arabandi, Ontopro
Kavishwar Wagholikar, Massachusetts General Hospital
Dina Demner-Fushman, National Library of Medicine
Jon Patrick, Health Language Analytics
Guergana Savova, Boston Children's Hospital
Ozlem Uzuner, SUNY
Chunhua Weng, Columbia University
Hua Xu, UTHealth
Pierre Zweigenbaum, LIMSI

Presentation Materials: