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A frozen CT-CLIP model can outperform traditional clinical baselines in lung cancer survival prediction, even with limited data.
Freeing survival prediction from reliance on expert-derived features, this model learns directly from CT scans and radiology reports to improve accuracy, especially when clinical data is scarce.
