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Demonstrates a novel prediction model for breast cancer, suggesting improved prognostic accuracy.
Breast cancer is one of the commonly occurring malignant tumors and poses a serious threat to women’s health. To address this important clinical problem, an innovative cross-modal graph neural network model, PreGAT, is proposed in this study. The model incorporates patient’s clinical features and constructed graph structural features to codify the complex topology of multi-source data through graph attention networks and attention mechanisms.
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Chang et al. (2024) studied this question.
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