Validity of evidence-based recommendations by a large language model for interdisciplinary board decisions in neurooncology: An explorative study and critical evaluation
The study finds that LLM-generated summaries can effectively emulate the style and structure of human-authored ones, indicating their promise as an additional tool in neuro-oncology. These AI models can enhance documentation quality and serve as valuable support in clinical settings. While further research is necessary to explore broader applications, LLMs offer exciting potential as a complement to traditional decision-making processes.
Authors
- Chiara Negwer (ORCID: https://orcid.org/0000-0003-2997-969X)
- Amir Kaywan Aftahy (ORCID: https://orcid.org/0000-0002-8897-2220)
- Arthur Wagner (ORCID: https://orcid.org/0000-0001-9947-2240)
- Jens Gempt (ORCID: https://orcid.org/0000-0003-4123-4690)
- Viktor Maria Eisenkolb
- Hanno S. Meyer (ORCID: https://orcid.org/0000-0002-4576-1239)
- Maria Goldberg (ORCID: https://orcid.org/0000-0002-0706-7529)
- Bernhard Meyer (ORCID: https://orcid.org/0000-0002-2846-8719)
Institutions
- Universität Hamburg (DE)
- TUM Klinikum (DE)
- International Neuroscience Institute (DE)
- University Medical Center Hamburg-Eppendorf (DE)
Publication Details
- Journal
- Digital Health
- Published
- 2025-05-01
- DOI
- https://doi.org/10.1177/20552076251384604
- Primary Topic
- Biomedical Text Mining and Ontologies
- Type
- article
- Field-Weighted Citation Impact
- 0.00