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Review
. 2022 Sep;3(9):1026-1038.
doi: 10.1038/s43018-022-00436-4. Epub 2022 Sep 22.

Artificial intelligence in histopathology: enhancing cancer research and clinical oncology

Artem Shmatko #  1   2 , Narmin Ghaffari Laleh #  3 , Moritz Gerstung  4   5 , Jakob Nikolas Kather  6   7   8   9
Affiliations
Review

Artificial intelligence in histopathology: enhancing cancer research and clinical oncology

Artem Shmatko et al. Nat Cancer. 2022 Sep.

Abstract

Artificial intelligence (AI) methods have multiplied our capabilities to extract quantitative information from digital histopathology images. AI is expected to reduce workload for human experts, improve the objectivity and consistency of pathology reports, and have a clinical impact by extracting hidden information from routinely available data. Here, we describe how AI can be used to predict cancer outcome, treatment response, genetic alterations and gene expression from digitized histopathology slides. We summarize the underlying technologies and emerging approaches, noting limitations, including the need for data sharing and standards. Finally, we discuss the broader implications of AI in cancer research and oncology.

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