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Predicting endometrial cancer subtypes and molecular features from histopathology images using multi-resolution deep learning models
The determination of endometrial carcinoma histological subtypes, molecular subtypes, and mutation status is critical for the diagnostic process, and directly affects patients’ prognosis and treatment. Sequencing, albeit slower and more expensive, can provide additional information on molecular subt...
Autores principales: | Hong, Runyu, Liu, Wenke, DeLair, Deborah, Razavian, Narges, Fenyö, David |
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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/PMC8484685/ https://www.ncbi.nlm.nih.gov/pubmed/34622237 http://dx.doi.org/10.1016/j.xcrm.2021.100400 |
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