Model evaluation helps in assessing the performance and generalizability of a model. In cancer diagnostics, an accurate model can differentiate between benign and malignant tumors, while in treatment, it can predict patient response to specific therapies. Without robust evaluation, models may provide misleading results, leading to incorrect clinical decisions.
