Journal Article (Review Article)

DKFZ-2022-02261

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Artificial intelligence in histopathology: enhancing cancer research and clinical oncology.

Shmatko, A. (First author)DKFZ* ; Ghaffari Laleh, N. ; Gerstung, M.DKFZ* ; Kather, J. N.

2022
Nature Research London

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Please use a persistent id in citations: doi:10.1038/s43018-022-00436-4

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.

Note: #EA:B450#

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Contributing Institute(s):

1. Künstl. Intelligenz in der Onkologie (B450)

Research Program(s):

1. 312 - Funktionelle und strukturelle Genomforschung (POF4-312) (POF4-312)

Appears in the scientific report 2022

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Database coverage:
; BIOSIS Previews ; Clarivate Analytics Master Journal List ; Current Contents - Clinical Medicine ; IF >= 20 ; JCR ; SCOPUS ; Web of Science Core Collection

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