Class imbalance problem?
As mentioned in the comments, your data doesn't have that much of an imbalance. A good way to check how the imbalance is affecting your model, is by calculating precision and recall. These values will be quite low while your accuracy will shoot high because it will predict the majority class for every sample. However the 'maybe normal' case is dangerous. It would be better to set a different threshold , probably a lower one so that even the marginally abnormal cases will be classified as abnormal. A precision recall curve or a ROC curve is a good way to decide on the cutoff.