Predicting Breast Cancer Events in Ductal Carcinoma In Situ (DCIS) Using Generative Adversarial Network Augmented Deep Learning Model

Predicting Breast Cancer Events in Ductal Carcinoma In Situ (DCIS) Using Generative Adversarial Network Augmented Deep Learning Model

Standard clinicopathological parameters (age, growth pattern, tumor size, margin status, and grade) have been shown to have limited value in predicting recurrence in ductal carcinoma in situ (DCIS) patients. Early and accurate recurrence prediction would facilitate a more aggressive treatment policy...

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Bibliographic Details
Main Authors: Soumya Ghose, Sanghee Cho, Fiona Ginty, Elizabeth McDonough, Cynthia Davis, Zhanpan Zhang, Jhimli Mitra, Adrian L. Harris, Aye Aye Thike, Puay Hoon Tan, Yesim Gökmen-Polar, Sunil S. Badve
Format: Article
Language:English
Published: MDPI AG 2023-03-01
Series:Cancers
Subjects:
DCIS
breast cancer events
risk-stratification
deep learning
Online Access:https://www.mdpi.com/2072-6694/15/7/1922

Internet

https://www.mdpi.com/2072-6694/15/7/1922

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