{
  "abstract": "LLMs accelerate medical information work, but speed of synthesis does not justify reliance. As T.S. Eliot asked, “Where is the knowledge we have lost in information?” Using a data-information-evidence-practice hierarchy, LLM outputs enter clinical setting as information and become evidence only through appraisal, validation, and contextual judgement. We highlight how LLMs can support evidence infrastructures, clarify evidence boundaries, and reshape clinical expertise to strengthen rather than replace evidence-based medicine.",
  "abstract_shown": true,
  "affiliations": [
    "Institute of Ophthalmology, University College London, London, UK",
    "Beijing Visual Science and Translational Eye Research Institute (BERI), Beijing Tsinghua Changgung Hospital Eye Center, School of Clinical Medicine, Tsinghua Medicine, Tsinghua University, Beijing, China",
    "Moorfields Eye Hospital NHS Foundation Trust, London, UK",
    "Oxford Eye Hospital, Oxford University NHS Foundation Trust, Oxford, UK",
    "NIHR Biomedical Research Centre at Moorfields Eye Hospital NHS Foundation Trust, London, UK",
    "School of Biomedical Engineering, Tsinghua Medicine, Tsinghua University, Beijing, China",
    "Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore"
  ],
  "article_type": "review article",
  "arxiv": null,
  "author_total": 5,
  "authors": [
    {
      "affs": [
        0,
        1
      ],
      "name": "Yilan Wu"
    },
    {
      "affs": [
        0,
        2,
        3,
        4
      ],
      "name": "Ariel Yuhan Ong"
    },
    {
      "affs": [
        0,
        4
      ],
      "name": "Kuang Hu"
    },
    {
      "affs": [
        1,
        5,
        6
      ],
      "name": "Tien Yin Wong"
    },
    {
      "affs": [
        0,
        4
      ],
      "name": "Pearse A. Keane"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/10x3fy0b6mv4w.bib",
  "cited_by": 1,
  "doi": "10.1038/s41746-026-02909-7",
  "fulltext_url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC13696673/",
  "id": "10x3fy0b6mv4w",
  "issns": [
    "2398-6352"
  ],
  "landing_url": "https://doi.org/10.1038/s41746-026-02909-7",
  "language": "en",
  "licence": "CC-BY-4.0",
  "licence_label": "CC BY 4.0",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "heading",
      "Perspective"
    ],
    [
      "openalex",
      "2718|Artificial Intelligence in Healthcare and Education"
    ]
  ],
  "openalex": "W7167265710",
  "pdf_url": "https://www.nature.com/articles/s41746-026-02909-7_reference.pdf",
  "pmcid": "PMC13696673",
  "pmid": "42399653",
  "published": "2026-07-03",
  "publisher": "Nature Publishing Group",
  "ris": "https://research.draconitic.com/paper/10x3fy0b6mv4w.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:17:59Z",
      "native_id": "PMC13696673",
      "source": "pmc",
      "url": "https://doi.org/10.1038/s41746-026-02909-7"
    }
  ],
  "subjects": [
    {
      "field": "medicine",
      "origin": "openalex:2718|Artificial Intelligence in Healthcare and Education",
      "subfield": "epidemiology-public-health"
    }
  ],
  "title": "Fast information and slow evidence in the large language models era",
  "title_text": "Fast information and slow evidence in the large language models era",
  "type": "peer-reviewed",
  "updated_at": "2026-10-30T12:33:58Z",
  "url": "https://research.draconitic.com/paper/10x3fy0b6mv4w",
  "venue": "NPJ Digital Medicine",
  "versions": []
}