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...

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Detalles Bibliográficos
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.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Article
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

Internet

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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