A computer-implemented method, comprising: accessing a plurality of treatment plans that have associated therewith perturbations of nominal values of parameters of the treatment plans; for each treatment field of the treatment plans, determining a field-specific planning target volume, fsPTV, based on the perturbations; accessing information that delineates at least one clinical target volume, CTV, and information that delineates at least one organ-at-risk, OAR, volume, wherein each said OAR volume comprises at least one sub-volume that is delineated based on spatial relationships between each said OAR volume and the CTV and the fsPTV for said each treatment field; and either: (a) determining dose distributions for each said sub-volume, wherein the dose distributions comprise a dose distribution based on the nominal values and dose distributions based on the perturbations; and generating dose prediction models for each said sub-volume, wherein the models comprise a model trained using the dose distribution based on the nominal values and models trained using the dose distributions based on the perturbations; or (b) determining a plurality of dose distributions comprising a dose distribution based on the nominal values and dose distributions based on the perturbations; and generating a dose prediction model for each said sub-volume, the model trained using the plurality of dose distributions. accessing a plurality of treatment plans that have associated therewith perturbations of nominal values of parameters of the treatment plans; for each treatment field of the treatment plans, determining a field-specific planning target volume, fsPTV, based on the perturbations; accessing information that delineates at least one clinical target volume, CTV, and information that delineates at least one organ-at-risk, OAR, volume, wherein each said OAR volume comprises at least one sub-volume that is delineated based on spatial relationships between each said OAR volume and the CTV and the fsPTV for said each treatment field; and either: (a) determining dose distributions for each said sub-volume, wherein the dose distributions comprise a dose distribution based on the nominal values and dose distributions based on the perturbations; and generating dose prediction models for each said sub-volume, wherein the models comprise a model trained using the dose distribution based on the nominal values and models trained using the dose distributions based on the perturbations; or (b) determining a plurality of dose distributions comprising a dose distribution based on the nominal values and dose distributions based on the perturbations; and generating a dose prediction model for each said sub-volume, the model trained using the plurality of dose distributions. (a) determining dose distributions for each said sub-volume, wherein the dose distributions comprise a dose distribution based on the nominal values and dose distributions based on the perturbations; and generating dose prediction models for each said sub-volume, wherein the models comprise a model trained using the dose distribution based on the nominal values and models trained using the dose distributions based on the perturbations; or (b) determining a plurality of dose distributions comprising a dose distribution based on the nominal values and dose distributions based on the perturbations; and generating a dose prediction model for each said sub-volume, the model trained using the plurality of dose distributions. <EOS>