A healthcare organization is developing an ML model to predict whether patients are at risk of developing a rare but critical disease. Missing a patient with a disease (a false negative) could delay treatment, potentially leading to severe consequences. However, incorrectly predicting a disease (a false positive) may result in unnecessary follow-up tests, which are less costly compared to missing an actual case. Which model characteristic should the healthcare organization prioritize to best meet its requirements?