Accuracy is often evaluated through metrics such as sensitivity, specificity, and AUC-ROC curves. These metrics assess how well the machine learning model, with its assigned weights, can distinguish between cancerous and non-cancerous cases. Cross-validation and external validation sets are also used to ensure the model's generalizability.
