Privacy-preserving model evaluation for logistic and linear regression using homomorphically encrypted genotype data.

Our study demonstrates that it is possible to perform linear and logistic regression model evaluation while protecting patient confidentiality with theoretical security guarantees. Our implementation and test data are available at https://github.com/G2Lab/privateML/.