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External validation of AI models in health should be replaced with recurring local validation

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Acknowledgements

D.A.C. is funded by an RAEng Research Chair and a UK National Institute for Health and Care Research (NIHR) Research Professorship, the NIHR Oxford Biomedical Research Centre, the InnoHK Centre for Cerebro-cardiovascular Engineering and the Oxford Pandemic Sciences Institute. T.Z. was supported by the Royal Academy of Engineering under the Research Fellowship scheme.

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Authors and Affiliations

  1. Stanford Bioengineering Department, Stanford University, Stanford, CA, USA

    Alexey Youssef

  2. Department of Engineering Science, University of Oxford, Oxford, UK

    Alexey Youssef, Anshul Thakur, Tingting Zhu & David Clifton

  3. Duke University School of Medicine, Durham, NC, USA

    Michael Pencina

  4. Oxford–Suzhou Centre for Advanced Research, Suzhou, China

    David Clifton

  5. Center for Biomedical Informatics Research, Stanford University School of Medicine, Stanford, CA, USA

    Nigam H. Shah

  6. Technology and Digital Solutions, Stanford Medicine, Stanford, CA, USA

    Nigam H. Shah

  7. Clinical Excellence Research Center, Stanford Medicine, Stanford, CA, USA

    Nigam H. Shah

Authors
  1. Alexey Youssef
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  2. Michael Pencina
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  3. Anshul Thakur
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  4. Tingting Zhu
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  5. David Clifton
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  6. Nigam H. Shah
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Correspondence to Alexey Youssef.

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Youssef, A., Pencina, M., Thakur, A. et al. External validation of AI models in health should be replaced with recurring local validation. Nat Med 29, 2686–2687 (2023). https://doi.org/10.1038/s41591-023-02540-z

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