machine learning – Classification Model

I have a question with regards to classification:

Given a patient dataset, each patient belongs to one of the only two classes: patients with
diabetes, and patients without diabetes. A classification model is applied to this dataset, and the
the predictions are evaluated using accuracy and F-score. Suppose the probability of a patient with diabetes is 𝑑, where 0 ≤ 𝑑 ≤ 1. Consider two dummy models A and B. Model A always classifies a patient into the diabetes class. Model B classifies each patient randomly into one of the two classes with equal probability. What is the expected accuracy of each model?