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Summary
| Description |
English: Histopathology with identification of breast cancer by AI in a whole-slide image. H&E stain. Original caption: Example whole-slide images from test TCGA data cohort with predictions produced by the ConvNet classifier. |
| Date | |
| Source |
Cruz-Roa A, Gilmore H, Basavanhally A, Feldman M, Ganesan S, Shih NNC (2017). "Accurate and reproducible invasive breast cancer detection in whole-slide images: A Deep Learning approach for quantifying tumor extent.". Sci Rep 7: 46450. DOI:10.1038/srep46450. PMID 28418027. PMC: 5394452. "This work is licensed under a Creative Commons Attribution 4.0 International License." |
| Author | Cruz-Roa A, Gilmore H, Basavanhally A, Feldman M, Ganesan S, Shih NNC |
| Other versions |
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Licensing
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| Date/Time | Thumbnail | Dimensions | User | Comment | |
|---|---|---|---|---|---|
| current | 15:32, 23 February 2024 | | 633 × 547 (407 KB) | Mikael Häggström | Uploaded own work with UploadWizard |
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