Deep learning links histology, molecular signatures and prognosis in cancer
- PMID: 35122048
- PMCID: PMC11330634
- DOI: 10.1038/s43018-020-0099-2
Deep learning links histology, molecular signatures and prognosis in cancer
Abstract
Deep learning can be used to predict genomic alterations based on morphological features learned from digital histopathology. Two independent pan-cancer studies now show that automated learning from digital pathology slides and genomics can potentially decipher broader classes of molecular signatures and prognostic associations across cancer types.
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Pan-cancer image-based detection of clinically actionable genetic alterations.Nat Cancer. 2020 Aug;1(8):789-799. doi: 10.1038/s43018-020-0087-6. Epub 2020 Jul 27. Nat Cancer. 2020. PMID: 33763651 Free PMC article.
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Pan-cancer computational histopathology reveals mutations, tumor composition and prognosis.Nat Cancer. 2020 Aug;1(8):800-810. doi: 10.1038/s43018-020-0085-8. Epub 2020 Jul 27. Nat Cancer. 2020. PMID: 35122049
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