Project Grant 2442172

Award Date 6/15/25
Completion Date 5/31/30
Dollars Obligated $348K
Federal Grant Program
47.070
Assistance Type
Project Grant
Place of Performance
Atlanta, GA 30322, USA
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This $347,570 Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) aims to develop a systematic framework called "Knowledge Graphs-Large Language Model Co-Learning (KG-LLM Co-Learning)" to address challenges in using large language models (LLMs) and knowledge graphs (KGs) for healthcare applications.

The key products and services to be delivered include:

  1. Novel LLM-based methods for constructing comprehensive healthcare KGs by unifying existing KGs, continuously improving KGs based on biomedical literature, and enriching KGs using multi-modal patient data.
  2. Novel usage of KGs to enhance the planning, reasoning, and grounding capabilities of healthcare LLMs.
  3. Exploring a federated multi-agent system to integrate LLMs and data while addressing data privacy, human values, and broader health factors.
  4. Comprehensive evaluations of the healthcare applications of risk prediction, treatment suggestion, and disease subtyping using de-identified patient data.

The award recipient is Emory University, a private research university in Atlanta, Georgia. The project period is from Jun 15, 2025 to May 31, 2030.

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