Creating Biomedical Technologies to Improve Health

NEWS & EVENTS

Language Processing: State of the Art, Future Directions and Applications for Enhancing Clinical Decision-Making

Monday, April 23, 2012 (All day) to Tuesday, April 24, 2012 (All day)
Lister Hill Auditorium (Building 38A), NIH main campus in Bethesda, MD

The goals of the workshop sponsored by the National Library of Medicine and the National Institute of Biomedical Imaging and Bioengineering are to identify the current state of the art, grand challenges and specific roadblocks and to identify effective use and best practices. This workshop will be of interest to researchers in the fields of natural language processing and clinical decision support, clinicians, hospital administrators, information technology companies and entrepreneurs, and government employees involved with electronic medical records and free-text analysis. REGISTRATION IS REQUIRED.

This NIH sponsored workshop will not be videocast.

For more information, please contact Thomas Rindflesch at trindflesch@mail.nih.gov 301-435-3191

Program Area: 
Meeting summaries and reports: 

On behalf of the National Library of Medicine (NLM) and the National Institute of Biomedical Imaging and Bioengineering (NIBIB), we invite you to participate in the upcoming NIH workshop on "Natural Language Processing: State of the Art, Future Directions and Applications for Enhancing Clinical Decision-Making." The workshop will be held over two full days, April 23-24, 2012 at Lister Hill Auditorium on the NIH main campus in Bethesda, MD.

The first day is focused on reviewing the current state of the art in natural language processing (NLP) issues and is hosted by NLM. The sessions will consider text in English, both in biomedicine and outside that domain, and discuss strategies that are innovative, principled, and hold significant promise (in robustness, generality, and accuracy) in the field.

On the morning of the second day, activities sponsored by NLM to make specific proposals for NLP research will run in parallel with sessions hosted by NIBIB, which will address the promise and application of natural language processing in clinical decision support (CDS). The presentations will be given by a wide range of perspectives on the potential impact of natural language processing, including from the provider, vendor, patient, payer and government perspectives. The afternoon of the second day will be solely devoted to these topics.

Goals of the Workshop
he goals of the workshop are to identify the current state of the art, grand challenges and specific roadblocks and to identify effective use and best practices. A practical outcome of this workshop will be specific recommendations for a research agenda intended to achieve progress in the field. NLM in particular seeks to elicit ideas for, and discussion about, a research agenda in NLP that:

  • is a principled approach that will robustly generalize
  • exploits the structure of language and ontology
  • combines symbolic with statistical methods
  • exploits the structure of language and ontology, including those of a specific domain

Poster Session
The poster session will be focused on the promise and applications of natural language processing (NLP) in clinical decision support (CDS). Posters will include a wide range of perspectives on the potential impact of NLP to help healthcare providers, academicians, vendors, patient advocates, payers and government agencies and patients to

  • improve accuracy of clinical diagnosis,
  • prioritize evidences and test results,
  • provide optimal treatment recommendation,
  • identify the best practices,
  • effectively use evidence based and CER based guidelines, and
  • ultimately achieve a better healthcare outcome.

Who Should Attend
This workshop will be of interest to researchers in the fields of natural language processing and clinical decision support, clinicians, hospital administrators, information technology companies and entrepreneurs, and government employees involved with electronic medical records and free-text analysis.]