Systems and methods of radiomics based cancer stratification

A computer system, comprising:

• one or more processors;
• and
• a non-transitory computer-readable medium including computer-executable instructions that, when executed by the one or more processors, cause the processors to perform a method comprising:
• A) inputting information into an ensemble model comprising a plurality of component models to obtain as output from each respective component model in the plurality of component models a corresponding component prediction for the cancer condition, thereby obtaining a plurality of component predictions for the cancer condition, wherein:
• the information comprises, for each respective class of radiomics features in a plurality of classes of radiomics features, a corresponding value for each respective radiomic feature in a corresponding plurality of radiomics features of the respective class of radiomics features obtained from a medical imaging dataset, wherein the medical imaging dataset comprises a plurality of medical images of the tissue in the subject acquired at a first time using a first medical imaging modality,
• the ensemble model applies a plurality of parameters to the information through a plurality of computations, and
• the inputting includes (i) inputting the corresponding value for each respective radiomics feature in the corresponding plurality of radiomics features of a first respective class of radiomics features in the plurality of classes of radiomics features into a first respective component model in the plurality of component models and (ii) inputting the corresponding value for each respective radiomics feature in the corresponding plurality of radiomics features of a second respective class of radiomics features in the plurality of classes of radiomics features into a second respective component model in the plurality of component models, wherein the corresponding value for no respective radiomics feature in the corresponding plurality of radiomics features of the first respective class of radiomics features is input into the second component model and the corresponding value for no respective radiomics feature in the corresponding plurality of radiomics features of the second respective class of radiomics features is input into the first respective component model;
• and
• B) combining the plurality of component predictions to obtain as output of the ensemble model a characterization of the cancer condition.

A non-transitory computer-readable storage medium having stored thereon program code instructions that, when executed by a processor, cause the processor to perform a method comprising:

• A) inputting information into an ensemble model comprising a plurality of component models to obtain as output from each respective component model in the plurality of component models a corresponding component prediction for the cancer condition, thereby obtaining a plurality of component predictions for the cancer condition, wherein:
• the information comprises, for each respective class of radiomics features in a plurality of classes of radiomics features, a corresponding value for each respective radiomic feature in a corresponding plurality of radiomics features of the respective class of radiomics features obtained from a medical imaging dataset, wherein the medical imaging dataset comprises a plurality of medical images of the tissue in the subject acquired at a first time using a first medical imaging modality,
• the ensemble model applies a plurality of parameters to the information through a plurality of computations, and
• the inputting includes (i) inputting the corresponding value for each respective radiomics feature in the corresponding plurality of radiomics features of a first respective class of radiomics features in the plurality of classes of radiomics features into a first respective component model in the plurality of component models and (ii) inputting the corresponding value for each respective radiomics feature in the corresponding plurality of radiomics features of a second respective class of radiomics features in the plurality of classes of radiomics features into a second respective component model in the plurality of component models, wherein the corresponding value for no respective radiomics feature in the corresponding plurality of radiomics features of the first respective class of radiomics features is input into the second component model and the corresponding value for no respective radiomics feature in the corresponding plurality of radiomics features of the second respective class of radiomics features is input into the first respective component model;
• and
• B) combining the plurality of component predictions to obtain as output of the ensemble model a characterization of the cancer condition.