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Nephrology

Automating kidney transplant diagnostics

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Diagnosis of kidney allograft rejection remains complex and somewhat subjective; but an automated version of the gold-standard Banff classification could streamline assessment and improve diagnostic accuracy.

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Fig. 1: From precision diagnostic tools to improved kidney allograft patient care.

References

  1. Racusen, L. C. et al. Kidney Int. 55, 713–723 (1999).

    Article  CAS  PubMed  Google Scholar 

  2. Sis, B. et al. Am. J. Transplant. 10, 464–471 (2010).

    Article  CAS  PubMed  Google Scholar 

  3. Mengel, M. et al. Am. J. Transplant. 12, 563–570 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Loupy, A. et al. Am. J. Transplant. 20, 2318–2331 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Yoo, D. et al. Nat. Med. https://doi.org/10.1038/s41591-023-02323-6(2023).

  6. Webster, A. C. et al. Cochrane Database Syst. Rev. 7, CD004756 (2017).

    PubMed  Google Scholar 

  7. Wan, S. S. et al. Transplantation 102, 557–568 (2018).

    Article  PubMed  Google Scholar 

  8. Gupta, G. et al. Transplantation 97, 1240–1246 (2014).

    Article  CAS  PubMed  Google Scholar 

  9. Farris, A. B. et al. Am. J. Transplant. 20, 2392–2399 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

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Authors and Affiliations

  1. School of Biological Sciences, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre, University of Manchester, Manchester, UK

    Nissrin Alachkar

  2. School of Mathematics, Faculty of Science and Engineering, University of Manchester, Manchester, UK

    Nissrin Alachkar

  3. Department of Medicine, The Johns Hopkins University School of Medicine, Baltimore, MD, USA

    Nada Alachkar

Authors
  1. Nissrin Alachkar
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  2. Nada Alachkar
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Correspondence to Nada Alachkar.

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The authors declare no competing interests.

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Alachkar, N., Alachkar, N. Automating kidney transplant diagnostics. Nat Med 29, 1066–1067 (2023). https://doi.org/10.1038/s41591-023-02300-z

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