Augmented non-hallucinating large language models as medical information curators
Augmented non-hallucinating large language models as medical information curators
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London: Nature Publishing Group UK
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English
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London: Nature Publishing Group UK
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Reliably processing and interlinking medical information has been recognized as a critical foundation to the digital transformation of medical workflows, and despite the development of medical ontologies, the optimization of these has been a major bottleneck to digital medicine. The advent of large language models has brought great excitement, and...
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Augmented non-hallucinating large language models as medical information curators
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TN_cdi_doaj_primary_oai_doaj_org_article_e8615f07bedf4f98b2b8b47ad3a92a9b
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https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_e8615f07bedf4f98b2b8b47ad3a92a9b
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ISSN
2398-6352
E-ISSN
2398-6352
DOI
10.1038/s41746-024-01081-0
