Scalable recurrence graph network for stratifying RhoB texture dynamics in rectal cancer biopsies
The scalable recurrence graph network (SRGNet) is introduced in this paper to improve the accuracy of predicting five-year survival outcomes in rectal cancer patients by analyzing RhoB texture dynamics in biopsies. RhoB, a key biomarker assessed via immunohistochemistry, is crucial in predicting res...
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| Main Author: | |
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| Format: | Article |
| Language: | English |
| Published: |
AIP Publishing LLC
2025-03-01
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| Series: | APL Machine Learning |
| Online Access: | http://dx.doi.org/10.1063/5.0243636 |
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