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Automated quantification of levels of breast terminal duct lobular (TDLU) involution using deep learning
Convolutional neural networks (CNNs) offer the potential to generate comprehensive quantitative analysis of histologic features. Diagnostic reporting of benign breast disease (BBD) biopsies is usually limited to subjective assessment of the most severe lesion in a sample, while ignoring the vast maj...
Autores principales: | de Bel, Thomas, Litjens, Geert, Ogony, Joshua, Stallings-Mann, Melody, Carter, Jodi M., Hilton, Tracy, Radisky, Derek C., Vierkant, Robert A., Broderick, Brendan, Hoskin, Tanya L., Winham, Stacey J., Frost, Marlene H., Visscher, Daniel W., Allers, Teresa, Degnim, Amy C., Sherman, Mark E., van der Laak, Jeroen A. W. M. |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8770616/ https://www.ncbi.nlm.nih.gov/pubmed/35046392 http://dx.doi.org/10.1038/s41523-021-00378-7 |
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