The accuracy of predictive models in cancer depends on various factors, including the quality of the data, the complexity of the model, and the specific type of cancer being studied. While some models have shown high accuracy in specific contexts, the generalizability of these models to broader populations remains a challenge. Continuous validation and refinement are essential for improving their reliability.
