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Artificial intelligence

AI for breast cancer screening

Whether support from artificial intelligence (AI) models improves breast screening is a topic of research in national cancer screening programmes and clinical oncology. Three studies now show that AI tools can assist radiologists with evaluating mammograms, substantially reducing workloads and possibly improving screening performance.

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Fig. 1: Current standard approach and potential implementation of AI into the pathway for mammography scans evaluation.

References

  1. Aggarwal, A. et al. Lancet Oncol. 25, e6–e17 (2024).

    Article  PubMed  Google Scholar 

  2. Lång, K. et al. Lancet Oncol. 24, 936–944 (2023).

    Article  Google Scholar 

  3. Warren, L. et al. Nat. Cancer https://doi.org/10.1038/s43018-026-01128-z (2026).

    Article  PubMed  Google Scholar 

  4. Kelly, C. et al. Nat. Cancer https://doi.org/10.1038/s43018-026-01127-0 (2026).

    Article  Google Scholar 

  5. de Vries, C. et al. Nat. Cancer https://doi.org/10.1038/s43018-026-01126-1 (2026).

    Article  PubMed  Google Scholar 

  6. Freeman, K. et al. BMJ 374, n1872 (2021).

    Article  PubMed  Google Scholar 

  7. Yoon, J. H. et al. Radiology 307, e222639 (2023).

    Article  PubMed  Google Scholar 

  8. McKinney, S. M. et al. Nature 577, 89–94 (2020).

    Article  CAS  PubMed  Google Scholar 

  9. Taylor-Phillips, S. et al. Lancet Digit Health 4, e558–e565 (2022).

    Article  CAS  PubMed  Google Scholar 

  10. Tufail, A. et al. Ophthalmology 124, 343–351 (2017).

    Article  Google Scholar 

  11. Geppert, J. et al. Thorax 79, 1040–1049 (2024).

    Article  PubMed  PubMed Central  Google Scholar 

  12. Wu, T., Lucas, E., Zhao, F., Basu, P. & Qiao, Y. Cancer Biol. Med. 21, 864–879 (2024).

    PubMed  PubMed Central  Google Scholar 

  13. Vargas-Palacios, A., Sharma, N. & Sagoo, G. S. Nat. Commun. 14, 61 (2023).

    Article  Google Scholar 

  14. Gatting, L. et al. BMJ Public Health 2, e000892 (2024).

    Article  PubMed Central  Google Scholar 

Download references

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Correspondence to Allan Hackshaw.

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Hackshaw, A., Given-Wilson, R. AI for breast cancer screening. Nat Cancer 7, 402–404 (2026). https://doi.org/10.1038/s43018-025-01109-8

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