Machine learning model trained using artificial cell-free rna (cfrna) expression data

A system, comprising:

• at least one computer hardware processor;
• and
• at least one non-transitory computer-readable storage medium storing processor-executable instructions that, when executed by the at least one computer hardware processor, causes the at least one computer hardware processor to perform a method of predicting a characteristic of a subject based on cell-free RNA (cfRNA) expression data previously-obtained from a biological fluid sample from the subject, the method comprising:
• obtaining the cfRNA expression data;
• and
• processing the cfRNA expression data using a machine learning model trained to process cfRNA expression data from a subject and produce an output indicative of the characteristic of the subject,
• wherein the machine learning model was trained using artificial cfRNA expression data, the artificial cfRNA expression data comprising a plurality of artificial cfRNA expression profiles, an artificial cfRNA expression profile of the plurality of artificial cfRNA expression profiles having been generated by:
• generating a healthy expression profile component by:
• receiving a plurality of RNA expression profiles previously-obtained from biological samples from healthy subjects, the plurality of RNA expression profiles including a respective RNA expression profile for each of one or more cell types and/or each of one or more types of cell-containing samples;
• and
• generating the healthy expression profile component by combining the plurality of RNA expression profiles;
• generating a tumor expression profile component;
• and
• generating the artificial cfRNA expression profile by combining the healthy expression profile component and the tumor expression profile component.

At least one non-transitory computer-readable storage medium storing processor-executable instructions that, when executed by at least one computer hardware processor, causes the at least one computer hardware processor to perform a method of predicting a characteristic of a subject based on cell-free RNA (cfRNA) expression data previously-obtained from a biological fluid sample from the subject, the method comprising:

• obtaining the cfRNA expression data;
• and
• processing the cfRNA expression data using a machine learning model trained to process cfRNA expression data from a subject and produce an output indicative of the characteristic of the subject,
• wherein the machine learning model was trained using artificial cfRNA expression data, the artificial cfRNA expression data comprising a plurality of artificial cfRNA expression profiles, an artificial cfRNA expression profile of the plurality of artificial cfRNA expression profiles having been generated by:
• generating a healthy expression profile component by:
• receiving a plurality of RNA expression profiles previously-obtained from biological samples from healthy subjects, the plurality of RNA expression profiles including a respective RNA expression profile for each of one or more cell types and/or each of one or more types of cell-containing samples;
• and
• generating the healthy expression profile component by combining the plurality of RNA expression profiles;
• generating a tumor expression profile component;
• and
• generating the artificial cfRNA expression profile by combining the healthy expression profile component and the tumor expression profile component.