A Multiagent Summarization and Auto-Evaluation Framework for Medical Text: Development and Evaluation Study
This study highlights the potential of LLMs as reliable tools for unstructured medical data summarization and evaluation to reduce the dependency on human experts and also states the limitations. The proposed framework, multiagent summarization and auto-evaluation, demonstrates scalability and adaptability for clinical applications while addressing key challenges like hallucination and position bias.
Authors
- Bo Wen (ORCID: https://orcid.org/0000-0002-2017-1822)
- Farhana Zulkernine (ORCID: https://orcid.org/0000-0002-3326-0875)
- Yuhao Chen (ORCID: https://orcid.org/0009-0003-0605-0842)
Institutions
- Queen's University (CA)
- Lustgarten Foundation (US)
Publication Details
- Journal
- JMIR AI
- Published
- 2025-10-31
- DOI
- https://doi.org/10.2196/75932
- Citations
- 1
- Primary Topic
- Topic Modeling
- Type
- article
- Field-Weighted Citation Impact
- 2.48
Funders
- Cleveland Clinic
- Natural Sciences and Engineering Research Council of Canada