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Natural language processing (NLP) in the biomedical domain focuses on understanding of the domain specific language and aims to facilitate dissemination and exchange of scientific and other information important to the progress of medicine and to the public health.

The NLP Working Group focuses on all sub-domains of biomedical NLP, including but not limited to: clinical NLP -- natural language processing methods to support healthcare by operationalizing clinical information contained in clinical narrative; processing of scientific literature, as well as gray literature, such as drug labels and clinical guidelines; and social media.

Areas of interest to the NLP working group include, but are not limited to:

  • Recognition and extraction of health-related information from text
  • Clinical document analysis
  • Development of tools and approaches to biomedical text understanding
  • Applications of biomedical NLP in practice
  • Addressing text understanding needs of clinicians, researchers and consumers

Mission

The mission of the AMIA Natural Language Processing Working Group is to facilitate communication, collaboration, training, and networking for researchers who develop, apply, and promote natural language processing in biomedical science, patient care, public health and biomedical education.

Vision

The ultimate goal of Natural Language Processing, an area of artificial intelligence, is to enable computers to analyze and use natural language at the level required for a task, be it detecting patients’ cancer stages during chart review, deriving knowledge from the literature or patient authored social media content. The NLP-WG vision for NLP in the biomedical domain is to support biomedical sciences, patient care, public health and biomedical education in a valuable manner.

Goals

AMIA NLP-WG aims to foster biomedical NLP research and applications, build a community of biomedical NLP researchers and practitioners, and establish connections among the researchers and practitioners from different scientific backgrounds and countries.

Working Group Activities

Past, Present and Future

  • Working group calls
  • Face to face meetings at the fall Annual Symposium and the spring Summits
  • Pre-symposium meetings
  • Webinars
  • Journal club
  • Collaboration with groups both inside and outside AMIA
  • Identification and dissemination of relevant funding opportunities
  • Industry-academic collaborations
  • Academic guidance for early stage researchers, e.g. doctoral students

Leadership

Profile image for Rui Zhang, PhD, FAMIA

Rui Zhang, PhD, FAMIA

Chair 2025-2026
Professor and Founding Chief, Division of Computational Health Sciences, Medical School
University of Minnesota, Twin Cities
Profile image for Sunyang Fu, PhD, MHI

Sunyang Fu, PhD, MHI

Vice Chair 2025-2026
Assistant Professor
UTHealth
Profile image for Yanshan Wang, PhD

Yanshan Wang, PhD

Past Chair 2025
Assistant Professor and Vice Chair of Research
University of Pittsburgh
Profile image for Sujani Kakumanu, MD

Sujani Kakumanu, MD

Member-at-Large 2025-2026
CHIO
William S. Middleton Veterans Hospital
Profile image for Jiyeong Kim, PhD

Jiyeong Kim, PhD

Member-at-Large 2025-2026
Post doctoral scholar
Stanford University
Profile image for Xinsong Du, Ph.D.

Xinsong Du, Ph.D.

Secretary 2025-2026
Postdoctoral Research Fellow
Brigham and Women's Hospital/Harvard Medical School

 


  • Performing: Working Group has high level of engagement and output (workshops, papers, webinars)
  • Networking: Working Group has internal and external networking opportunities for members (mentorship programs, social events, collaboration)
  • Developing: New Working Group or revitalizing efforts to grow membership (recruitment efforts, leadership)
Phenotypes
Performing: 80%
Networking: 20%
Developing: 0%

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