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- W2804911165 abstract "Breast cancer (BC) is the most common cancer among women world-wide, approximately 20-25% of BCs are HER-2 positive. Analysis of HER-2 is fundamental to defining the appropriate therapy for patients with breast cancer. Inter-pathologist variability in the test results can affect diagnostic accuracy. The present study intends to propose an automatic scoring HER-2 algorithm. Based on color features, the technique is fully-automated and avoids segmentation, showing a concordance higher than 90% with a pathologist in the experiments realized." @default.
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- W2804911165 date "2018-05-14" @default.
- W2804911165 modified "2023-09-27" @default.
- W2804911165 title "An Automatic Patch-based Approach for HER-2 Scoring in Immunohistochemical Breast Cancer Images Using Color Features" @default.
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