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...
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| Main Authors: | , , |
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| Format: | Article (Journal) |
| Language: | English |
| Published: |
27 November 2024
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| In: |
npj digital medicine
Year: 2024, Volume: 7, Pages: 1-5 |
| ISSN: | 2398-6352 |
| DOI: | 10.1038/s41746-024-01344-w |
| Online Access: | Verlag, kostenfrei, Volltext: https://doi.org/10.1038/s41746-024-01344-w Verlag, kostenfrei, Volltext: https://www.nature.com/articles/s41746-024-01344-w 
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| Author Notes: | Lars Riedemann, Maxime Labonne & Stephen Gilbert |
| Summary: | 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. |
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| Item Description: | Gesehen am 23.05.2025 |
| Physical Description: | Online Resource |
| ISSN: | 2398-6352 |
| DOI: | 10.1038/s41746-024-01344-w |