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AI offers way to image and assess clinical cell samples

The use of artificial intelligence in the clinic to image slides of cells enables the rapid assessment of cellular characteristics that might help with diagnostic decisions.
By
  1. Yinuo Xu

    1. Yinuo Xu is in the Department of Computer and Information Science, University of Pennsylvania, Philadelphia, Pennsylvania 19104, USA.

  2. Zhi Huang

    1. Zhi Huang is in the Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, Pennsylvania 19104, USA.

Cellular-level information is routinely used as part of clinical diagnostics1. Laboratory workers use a microscope to inspect cells on glass slides to detect early signs of cancer in organs such as the lung and bladder. Although this method, called cytology, is a long-established diagnostic procedure, it has major weaknesses. Human interpretation is subjective and labour intensive, and workforce shortages are increasingly a challenge2. Writing in Nature, Nitta et al.3 present an artificial-intelligence approach that offers advantages over current methods in clinical cytology.

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doi: https://doi.org/10.1038/d41586-026-00288-3

References

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  3. Nitta, N. et al. Nature https://doi.org/10.1038/s41586-025-10094-y (2026).

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  9. Ding, T. et al. Nature Rev. Bioeng. 3, 890–907 (2025).

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Competing Interests

The authors declare no competing interests.

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