Large language models in healthcare
Large language models are increasingly used in clinical practice and are evolving from information retrieval tools towards agentic systems that support complex decision-making. Although key challenges remain, these models have the potential to reshape diagnostic workflows, improve clinical efficienc...
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| Main Authors: | , |
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| Format: | Article (Journal) |
| Language: | English |
| Published: |
23 March 2026
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| In: |
Nature reviews. Nephrology
Year: 2026, Pages: 1-2 |
| ISSN: | 1759-507X |
| DOI: | 10.1038/s41581-026-01071-3 |
| Online Access: | Verlag, lizenzpflichtig, Volltext: https://doi.org/10.1038/s41581-026-01071-3 Verlag, lizenzpflichtig, Volltext: https://www.nature.com/articles/s41581-026-01071-3 
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| Author Notes: | Daniel Truhn, Jakob Nikolas Kather |
| Summary: | Large language models are increasingly used in clinical practice and are evolving from information retrieval tools towards agentic systems that support complex decision-making. Although key challenges remain, these models have the potential to reshape diagnostic workflows, improve clinical efficiency and reduce health inequities. |
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| Item Description: | Gesehen am 30.04.2026 |
| Physical Description: | Online Resource |
| ISSN: | 1759-507X |
| DOI: | 10.1038/s41581-026-01071-3 |