Towards computationally efficient prediction of molecular signatures from routine histology images

Maxime W Lafarge¹, Viktor H Koelzer²

Affiliations

¹ Computational and Translational Pathology Group, Department of Pathology and Molecular Pathology, University Hospital and University of Zürich, Zürich CH-8091, Switzerland.
² Computational and Translational Pathology Group, Department of Pathology and Molecular Pathology, University Hospital and University of Zürich, Zürich CH-8091, Switzerland. Electronic address: viktor.koelzer@usz.ch.

PMID: 34686475
DOI: 10.1016/S2589-7500(21)00232-6

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Towards computationally efficient prediction of molecular signatures from routine histology images

Maxime W Lafarge et al. Lancet Digit Health. 2021 Dec.

Free article

. 2021 Dec;3(12):e752-e753.

doi: 10.1016/S2589-7500(21)00232-6. Epub 2021 Oct 19.

Authors

Maxime W Lafarge¹, Viktor H Koelzer²

Affiliations

¹ Computational and Translational Pathology Group, Department of Pathology and Molecular Pathology, University Hospital and University of Zürich, Zürich CH-8091, Switzerland.
² Computational and Translational Pathology Group, Department of Pathology and Molecular Pathology, University Hospital and University of Zürich, Zürich CH-8091, Switzerland. Electronic address: viktor.koelzer@usz.ch.

PMID: 34686475
DOI: 10.1016/S2589-7500(21)00232-6

No abstract available

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Conflict of interest statement

We declare no competing interests.

Comment on

Development and validation of a weakly supervised deep learning framework to predict the status of molecular pathways and key mutations in colorectal cancer from routine histology images: a retrospective study.
Bilal M, Raza SEA, Azam A, Graham S, Ilyas M, Cree IA, Snead D, Minhas F, Rajpoot NM. Bilal M, et al. Lancet Digit Health. 2021 Dec;3(12):e763-e772. doi: 10.1016/S2589-7500(21)00180-1. Epub 2021 Oct 19. Lancet Digit Health. 2021. PMID: 34686474 Free PMC article.

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Towards computationally efficient prediction of molecular signatures from routine histology images

Affiliations

Towards computationally efficient prediction of molecular signatures from routine histology images

Authors

Affiliations

Conflict of interest statement

Comment on

Publication types

MeSH terms

Grants and funding

LinkOut - more resources

Full Text Sources