Final answer:
The neural network uses the sigmoid function as the activation function for all nodes to determine the probability of a person having the disease.
Step-by-step explanation:
The statement states that the sigmoid function is used as the activation function for all nodes in a neural network. The output nodes indicate whether or not a person has the disease, with c1 representing 'no' and c2 representing 'yes'. Since the sigmoid function is used, the output of each node will be between 0 and 1, representing the probability of the person having the disease. In this case, if the output of the c1 node is greater than 0.5, it means the network predicts the person doesn't have the disease. If the output of the c2 node is greater than 0.5, it means the network predicts the person has the disease.
Therefore, the statement is true.