Techniques for solving the problem with an unbalanced data set

I am trying to solve a problem with an unbalanced data set. I have two classes, one is for patients with risk 1, the other for patients without risk 0.

I have a much larger number of patients without risk. For analysis, I used methods such as RandomOverSampler, SMOTE, ADASYN, Borderline-SMOTE, RandomUnderSampler, TomekLinks, NearMiss, SMOTEENN and SMOTETomek. In addition to resampling and subsampling, I would also like to try other techniques for solving the problem with an unbalanced data set. What other techniques can I try? For example ensemble technique, weighting classes and what else?