The path forward for large language models in medicine is open
Large language models (LLMs) are increasingly applied in medical documentation and have been proposed for clinical decision support. We argue that the future for LLMs in medicine must be based on transparent and controllable open-source models. Openness enables medical tool developers to control the safety and quality of underlying AI models, while also allowing healthcare professionals to hold these models accountable. For these reasons, the future is open.
Authors
- Lars Riedemann (ORCID: https://orcid.org/0000-0002-9510-1845)
- Stephen Gilbert (ORCID: https://orcid.org/0000-0002-1997-1689)
- Maxime Labonne
Institutions
- Heidelberg University (DE)
- University Hospital Heidelberg (DE)
- Liquidia Technologies (United States) (US)
- Technische Universität Dresden (DE)
Publication Details
- Journal
- npj Digital Medicine
- Published
- 2024-11-27
- DOI
- https://doi.org/10.1038/s41746-024-01344-w
- Citations
- 45
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 5.41
Funders
- European Commission
- Bundesministerium für Bildung und Forschung