Can you provide an example of a situation where minimizing a Type II error is particularly important?

Consider a medical test for a serious disease. A Type II error (failing to detect the disease) could have devastating consequences for the patient. Therefore, researchers would prioritize minimizing the risk of a Type II error, even if it means accepting a slightly higher risk of a Type I error (false positive).