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Predicting Breast Cancer Events in Ductal Carcinoma In Situ (DCIS) Using Generative Adversarial Network Augmented Deep Learning Model
SIMPLE SUMMARY: Ductal carcinoma in situ (DCIS) patients have an excellent overall survival rate and over-treatment is always a cause for concern due to potential side-effects. Standard clinicopathological parameters have limited value in predicting breast cancer events (BCEs) and stratification of...
Autores principales: | Ghose, Soumya, Cho, Sanghee, Ginty, Fiona, McDonough, Elizabeth, Davis, Cynthia, Zhang, Zhanpan, Mitra, Jhimli, Harris, Adrian L., Thike, Aye Aye, Tan, Puay Hoon, Gökmen-Polar, Yesim, Badve, Sunil S. |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10093091/ https://www.ncbi.nlm.nih.gov/pubmed/37046583 http://dx.doi.org/10.3390/cancers15071922 |
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