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Development of AI-based pathology biomarkers in gastrointestinal and liver cancer

Nature Reviews Gastroenterology & Hepatology volume 17, pages 591–592 (2020)Cite this article

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Deep learning can mine clinically useful information from histology. In gastrointestinal and liver cancer, such algorithms can predict survival and molecular alterations. Once pathology workflows are widely digitized, these methods could be used as inexpensive biomarkers. However, clinical translation requires training interdisciplinary researchers in both programming and clinical applications.

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Authors and Affiliations

  1. Department of Gastroenterology, University Hospital RWTH Aachen, Aachen, Germany

    Jakob N. Kather

  2. Department of Pathology, Henri Mondor University Hospital, Créteil, France

    Julien Calderaro

Authors
  1. Jakob N. Kather
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  2. Julien Calderaro
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Correspondence to Jakob N. Kather.

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Competing interests

J.N.K. has an informal, unpaid advisory role at Pathomix (Heidelberg, Germany). J.C. receives consulting fees from Owkin, Inc. (New York, NY, USA) and Crosscope (San Francisco, CA, USA).

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Kather, J.N., Calderaro, J. Development of AI-based pathology biomarkers in gastrointestinal and liver cancer. Nat Rev Gastroenterol Hepatol 17, 591–592 (2020). https://doi.org/10.1038/s41575-020-0343-3

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