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Obtaining spatially resolved tumor purity maps using deep multiple instance learning in a pan-cancer study
Tumor purity is the percentage of cancer cells within a tissue section. Pathologists estimate tumor purity to select samples for genomic analysis by manually reading hematoxylin-eosin (H&E)-stained slides, which is tedious, time consuming, and prone to inter-observer variability. Besides, pathol...
Autores principales: | Oner, Mustafa Umit, Chen, Jianbin, Revkov, Egor, James, Anne, Heng, Seow Ye, Kaya, Arife Neslihan, Alvarez, Jacob Josiah Santiago, Takano, Angela, Cheng, Xin Min, Lim, Tony Kiat Hon, Tan, Daniel Shao Weng, Zhai, Weiwei, Skanderup, Anders Jacobsen, Sung, Wing-Kin, Lee, Hwee Kuan |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8848022/ https://www.ncbi.nlm.nih.gov/pubmed/35199060 http://dx.doi.org/10.1016/j.patter.2021.100399 |
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