Deep learning analysis of hematoxylin and eosin-stained benign breast biopsies to predict future invasive breast cancer.
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| Title: | Deep learning analysis of hematoxylin and eosin-stained benign breast biopsies to predict future invasive breast cancer. |
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| Authors: | Saha M; Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Rockville, MD, United States., Abubakar M; Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Rockville, MD, United States., Pfeiffer RM; Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Rockville, MD, United States., Rohan TE; Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, United States., Duggan MA; Department of Pathology and Laboratory Medicine, University of Calgary, Calgary, AB, Canada., Richert-Boe K; Kaiser Permanente Center for Health Research, Portland, OR, United States., Almeida JS; Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Rockville, MD, United States., Gierach GL; Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Rockville, MD, United States. |
| Source: | JNCI cancer spectrum [JNCI Cancer Spectr] 2025 Apr 30; Vol. 9 (3). |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: Oxford University Press Country of Publication: England NLM ID: 101721827 Publication Model: Print Cited Medium: Internet ISSN: 2515-5091 (Electronic) Linking ISSN: 25155091 NLM ISO Abbreviation: JNCI Cancer Spectr Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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