Knowledge Representation and Semantics Working Group Pre-Symposium at AMIA 2023


The 2023 AMIA Knowledge Representation and Semantics Working Group Pre-Symposium workshop will be held on Saturday, Nov 11, 2023 8:30 AM - 12:00 PM CST as part of the 2023 American Medical Informatics Association Annual Symposium.

The objective of this pre-symposium collaborative workshop is to enhance awareness of knowledge representation and semantics approaches within biomedical informatics; to provide a venue to disseminate new developments in the field; and to facilitate new collaborations.

This instance of the workshop will include a special focus on knowledge representation approaches in combination with other artificial intelligence approaches, and will feature a panel of informaticists engaged in this effort.

Panelists include:

We invite submissions of two-page abstracts for podium talks on research and applications of knowledge representation approaches across the breadth of the biomedical informatics domain areas. Previous instances of the workshop have included diverse submissions and presentations on knowledge representation work in many areas of informatics, including:

The 2023 workshop will have a special emphasis on AI for health projects that combine knowledge representation and semantics approaches with complementary work in the areas of machine learning, deep learning, and natural language processing with large language models. Submissions specifically about KRS in AI for health will be presented in their own session followed by a panel-led open discussion of the topic.

Workshop Schedule

Learning Objectives:

After participating in this session, attendees should be better able to:

  1. Understand the state of the art in knowledge representation and semantics in biomedicine.
  2. Appreciate the breadth of the field, including works published/presented in venues other than AMIA.
  3. Foster potential new collaborations among researchers who have similar research interests.
  4. Understand and discuss applications of knowledge representation and semantics approaches as part of the larger effort to bring artificial intelligence solutions to biomedical