In the context of cancer research, overfitting can lead to models that appear to perform exceptionally well during the training phase but fail to generalize to new patients or datasets. This is problematic because it can result in inaccurate diagnoses, ineffective treatment plans, and ultimately, adverse outcomes for patients.
