GANs for latent space visualizations
AssigneeTempus AI, Inc.
InventorRyan Mork
Life of this patent
Estimating the term…
Abstract
The disclosure provides a method of analyzing a patient. The method includes receiving a plurality of latent space representations of patient data including genetic data associated with a plurality of patients, providing each of the plurality of latent space representations to a trained model, receiving a plurality of images from the trained model, each image included in the plurality of images being associated with a patient included in the plurality of patients, grouping at least a portion of the plurality of images into a plurality of groups, and displaying the plurality of groups to at least one user.
Claims20
A method of analyzing a subject, the method comprising:
- receiving first genetic data comprising at least one of RNA data or DNA data associated with a subject;
- applying a machine learning model or a dimensionality reduction algorithm to the first genetic data to generate second genetic data having a lower dimensionality than the first genetic data;
- providing the second genetic data to a trained model;
- receiving a subject image generated by the trained model using the second genetic data;
- identifying a pattern in the subject image that is present in at least one other image in a set of images generated by the trained model;
- providing the subject image to an analysis engine;
- receiving subject information from the analysis engine;
- and
- causing the subject information to be output to at least one of a medical practitioner or a memory.
A system for analyzing a subject, the system comprising:
- at least one memory;
- and
- at least one processor coupled to the at least one memory, the system configured to cause the at least one processor to execute instructions stored in the at least one memory to:
- receive first genetic data comprising at least one of RNA data or DNA data associated with a subject;
- generate apply a machine learning model or a dimensionality reduction algorithm to the first genetic data to generate second genetic data having a lower dimensionality than the first genetic data;
- provide the second genetic data to a trained model;
- receive a subject image generated by the trained model using the second genetic data;
- identify a pattern in the subject image that is present in at least one other image in a set of images generated by the trained model;
- provide the subject image to an analysis engine;
- receive subject information from the analysis engine;
- and
- cause the subject information to be output to at least one of a medical practitioner or a memory.
A computer program product for analyzing a subject, the computer program product comprising instructions stored on a non-transitory computer readable medium to cause at least one processor to:
- receive first genetic data comprising at least one of RNA data or DNA data associated with a subject;
- apply a machine learning model or a dimensionality reduction algorithm to the first genetic data to generate second genetic data having a lower dimensionality than the first genetic data;
- provide the second genetic data to a trained model;
- receive a subject image generated by the trained model using the second genetic data;
- identify a pattern in the subject image that is present in at least one other image in a set of images generated by the trained model;
- provide the subject image to an analysis engine;
- receive subject information from the analysis engine;
- and
- cause the subject information to be output to at least one of a medical practitioner or a memory.
Dependencies are inferred from the claim text.