A method for performing privacy based radiotherapy treatment planning, the method comprising: receiving, by processor circuitry, a medical image of a patient; processing, by the processor circuitry, the medical image with a student machine learning model to estimate one or more radiotherapy plan parameters, wherein the student machine learning model is trained to establish a relationship between a plurality of public training medical images and corresponding radiotherapy plan parameters of the public training medical images, wherein the radiotherapy plan parameters of the plurality of public training medical images are generated by: aggregating a plurality of radiotherapy plan parameter estimates which have been produced by: processing the plurality of public training medical images with a plurality of teacher machine learning models to generate sets of radiotherapy plan parameter estimates; and reducing respective dimensions of the sets of radiotherapy plan parameter estimates or the plurality of public training medical images; and perturbing the aggregated plurality of radiotherapy plan parameter estimates in accordance with a privacy criteria; increasing a dimension of the perturbed aggregated reduced dimension radiotherapy plan parameter estimates to output the plurality of radiotherapy plan parameters; and generating, by the processor circuitry, a radiotherapy treatment plan for the patient based on the estimated one or more radiotherapy plan parameters of the medical image of the patient. receiving, by processor circuitry, a medical image of a patient; processing, by the processor circuitry, the medical image with a student machine learning model to estimate one or more radiotherapy plan parameters, wherein the student machine learning model is trained to establish a relationship between a plurality of public training medical images and corresponding radiotherapy plan parameters of the public training medical images, wherein the radiotherapy plan parameters of the plurality of public training medical images are generated by: aggregating a plurality of radiotherapy plan parameter estimates which have been produced by: processing the plurality of public training medical images with a plurality of teacher machine learning models to generate sets of radiotherapy plan parameter estimates; and reducing respective dimensions of the sets of radiotherapy plan parameter estimates or the plurality of public training medical images; and perturbing the aggregated plurality of radiotherapy plan parameter estimates in accordance with a privacy criteria; aggregating a plurality of radiotherapy plan parameter estimates which have been produced by: processing the plurality of public training medical images with a plurality of teacher machine learning models to generate sets of radiotherapy plan parameter estimates; and reducing respective dimensions of the sets of radiotherapy plan parameter estimates or the plurality of public training medical images; and processing the plurality of public training medical images with a plurality of teacher machine learning models to generate sets of radiotherapy plan parameter estimates; and reducing respective dimensions of the sets of radiotherapy plan parameter estimates or the plurality of public training medical images; and perturbing the aggregated plurality of radiotherapy plan parameter estimates in accordance with a privacy criteria; increasing a dimension of the perturbed aggregated reduced dimension radiotherapy plan parameter estimates to output the plurality of radiotherapy plan parameters; and generating, by the processor circuitry, a radiotherapy treatment plan for the patient based on the estimated one or more radiotherapy plan parameters of the medical image of the patient.