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Analysis of CT Image Features of CcRCC on The Basis of Machine Learning: Differentiation of High-Grade from Low-Grade Fuhrman Nuclear Grades

2025-11-11

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<title>Abstract</title> <p>Previous researches have clarified clinical applications of radiomics-based prediction of tumor phenotype. The purpose of our research is to utilize radiomic features in computer-aided diagnosis (CAD) system of prediction for high and low Fuhrman nuclear grades (FNG) in clear cell renal cell carcinoma (ccRCC). We selected 110 images from 109 cases of axial contrast- enhanced computed to...

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Literature Corpus work
a222dff8-ef62-53af-a758-dcfeba60cc71
DOI
10.21203/rs.3.rs-5828567/v1
Open publication

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Analysis of CT Image Features of CcRCC on The Basis of Machine Learning: Differentiation of High-Grade from Low-Grade Fuhrman Nuclear GradesDOI 10.21203/rs.3.rs-5828567/v1
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