A whole slide image-based machine learning approach to predict ductal carcinoma in situ (DCIS) recurrence risk

A whole slide image-based machine learning approach to predict ductal carcinoma in situ (DCIS) recurrence risk

Abstract Background Breast ductal carcinoma in situ (DCIS) represent approximately 20% of screen-detected breast cancers. The overall risk for DCIS patients treated with breast-conserving surgery stems almost exclusively from local recurrence. Although a mastectomy or adjuvant radiation can reduce r...

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Bibliographic Details
Main Authors: Sergey Klimov, Islam M. Miligy, Arkadiusz Gertych, Yi Jiang, Michael S. Toss, Padmashree Rida, Ian O. Ellis, Andrew Green, Uma Krishnamurti, Emad A. Rakha, Ritu Aneja
Format: Article
Language:English
Published: BMC 2019-07-01
Series:Breast Cancer Research
Subjects:
DCIS
Digital image analysis
Prognosis
Machine learning
Recurrence prediction
Biomarker
Online Access:http://link.springer.com/article/10.1186/s13058-019-1165-5

Internet

http://link.springer.com/article/10.1186/s13058-019-1165-5

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