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Dynamic hypergraph representation for bone metastasis analysis
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DOI：10.1016/j.cmpb.2025.108966.png)
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Abstract
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• Dynamic hypergraph representation captures high-order relationships for bone metastasis analysis. • Nonlinear transformation and Gumbel-Softmax yield efficient, end-to-end hyperedge construction. • Outperforms baselines on large-scale bone metastasis datasets and public datasets. • Enhances interpretability and generalization with robust design and analyses.
Keywords:
Bone metastasis
Regions of interest
Multiple instance learning
Dynamic hypergraph construction
Hypergraph convolutional network
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