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This is a Quantitative Study study.

October 7, 2025Open Access

Tabular Foundation Model for Breast Cancer Prognosis using Gene Expression Data

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Novel framework predicts survival outcomes in breast cancer patients, highlighting machine learning advantages and accuracy.

TabSurv achieves superior performance in breast cancer prognosis across multiple datasets, improving survival prediction accuracy.
The model offers competitive advantages over traditional Cox models and machine learning approaches, simplifying computations.
Concordance index evaluation demonstrates both precision and robustness of TabSurv in predicting survival outcomes.
Benchmarked against state-of-the-art methods, TabSurv shows the best results in six datasets, emphasizing its efficiency.

Vu et al. (2025) studied this question.

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