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1. (WO2018227154) SYSTEMS, METHODS, AND COMPUTER-READABLE MEDIA FOR GENE AND GENETIC VARIANT PRIORITIZATION
Note: Text based on automatic Optical Character Recognition processes. Please use the PDF version for legal matters

WHAT IS CLAIMED IS:

1. An electronic image processing system for identifying one or more unknown genetic disorders by analyzing a series of pixels in a plurality of images of external soft tissue, the electronic image processing system comprising:

at least one memory for storing computer-executable instructions; and

at least one processor configured to execute the stored instructions to:

identify a first individual with an unknown genetic disorder by analysis of first electronic data reflective of first values corresponding to pixels of an external soft tissue image of the first individual, wherein the first values correspond to relationships between at least one group of pixels in the external soft tissue image of the first individual;

identify a second individual with another unknown genetic disorder by analysis of second electronic data reflective second values corresponding to second pixels of an external soft tissue image of the second individual, wherein the second values correspond to relationships between at least one group of pixels in the external soft tissue image of the second individual;

compare at least some of the analyzed data of the first individual with at least some of the analyzed data of the second individual; and

determine that the first individual and the second individual are likely to share the unknown genetic disorder.

2. The system of claim 1 , wherein determining that the first individual and the second individual are likely to share the unknown genetic disorder occurs without identifying the unknown genetic disorder.

3. The system of claim 1 , wherein the at least one processor is further configured to receive genetic data from each of the first individual and the second individual and, based on the received genetic data, determine that the first and second individuals share common genetic anomalies.

4. The system of claim 2, wherein the at least one processor is further configured to identify the unknown genetic disorder as a new disease based on the common genetic anomalies.

5. The system of claim 1 , wherein the at least one processor is further configured to cluster the first and second individuals into a common group likely to share the unknown genetic disorder.

6. The system of claim 1 , wherein the at least one processor is further configured to:

identify a plurality of additional individuals with the unknown genetic disorder by:

analysis of additional electronic data reflective of additional values corresponding to additional pixels of additional external soft tissue images of the plurality of additional individuals, and

comparison of at least some of the analyzed data for the additional individuals to the analyzed data of at least one of the first and the second individual.

7. The system of claim 6, wherein the at least one processor is further configured to cluster the plurality of additional individuals with the first individual and the second individual into a common group likely to share the unknown genetic disorder.

8. The system of claim 1 , wherein the at least one processor is further configured to compare at least some of the analyzed data of the first individual and the analyzed data of the second individual by comparing pixel intensity in corresponding regions of the electronic data for each of the first and second individual.

9. The system of claim 1 , wherein the at least one processor is further configured to recommend a treatment for at least one of the first individual and the second individual based on the determination that the first individual and the second individual are likely to share the same genetic disorder.

10. The system of claim 9, wherein the treatment recommended for the first individual is a treatment regimen of the second individual corresponding to an improvement in one or more symptoms experienced by the second individual.

1 1. The system of claim 1 , wherein the at least one processor is further configured to identify one or more comparable genetic disorders comparable to the unknown genetic disorder based on a comparison of one or more symptoms of at least one of the first and second individuals and one or more symptoms characteristic of the one or more comparable genetic disorders.

12. A computer-implemented method for identifying one or more unknown genetic disorders by analyzing a series of pixels in a plurality of images of external soft tissue, the method comprising: identifying a first individual with an unknown genetic disorder by analysis of first electronic data reflective of first values corresponding to pixels of an external soft tissue image of the first individual, wherein the first values correspond to relationships between at least one group of pixels in the external soft tissue image of the first individual;

identifying a second individual with another unknown genetic disorder by analysis of second electronic data reflective second values corresponding to second pixels of an external soft tissue image of the second individual, wherein the second values correspond to relationships between at least one group of pixels in the external soft tissue image of the second individual;

comparing at least some of the analyzed data of the first individual with at least some of the analyzed data of the second individual; and

determining that the first individual and the second individual are likely to share the unknown genetic disorder.

13. The method of claim 12, wherein determining that the first individual and the second individual are likely to share the unknown genetic disorder occurs without identifying the unknown genetic disorder.

14. The method of claim 12, further comprising:

receiving genetic data from each of the first individual and the second individual; and based on the received genetic data, determining that the first and second individuals share common genetic anomalies.

15. The method of claim 14, further comprising identifying the unknown genetic disorder as a new disease based on the common genetic anomalies.

16. The method of claim 12, further comprising clustering the first and second individuals into a common group likely to share the unknown genetic disorder.

17. The method of claim 12, further comprising:

identifying a plurality of additional individuals with the unknown genetic disorder by:

analysis of additional electronic data reflective of additional values corresponding to additional pixels of additional external soft tissue images of the plurality of additional individuals, and

comparison of at least some of the analyzed data for the additional individuals to the analyzed data of at least one of the first and the second individual.

18. The method of claim 17, further comprising clustering the plurality of additional individuals with the first individual and the second individual into a common group likely to share the unknown genetic disorder.

19. The method of claim 12, further comprising comparing at least some of the analyzed data of the first individual and the analyzed data of the second individual by comparing pixel intensity in corresponding regions of the electronic data for each of the first and second individual.

20. The method of claim 12, further comprising determining that the unknown genetic disorder and the another unknown genetic disorder are the same disorder.

21. A non-transitory, computer-readable medium storing instructions for identifying one or more unknown genetic disorders by analyzing a series of pixels in a plurality of images of external soft tissue, the instructions causing one or more processors to:

identify a first individual with an unknown genetic disorder by analysis of first electronic data reflective of first values corresponding to pixels of an external soft tissue image of the first individual, wherein the first values correspond to relationships between at least one group of pixels in the externa! soft tissue image of the first individual;

identify a second individual with another unknown genetic disorder by analysis of second electronic data reflective second values corresponding to second pixels of an external soft tissue image of the second individual, wherein the second values correspond to relationships between at least one group of pixels in the external soft tissue image of the second individual;

compare at least some of the analyzed data of the first individual with at least some of the analyzed data of the second individual; and

determine that the first individual and the second individual are likely to share the unknown genetic disorder.

22. An electronic image processing system for identifying genetic disorders by analyzing a series of pixels in a plurality of images of external soft tissue, the electronic image processing system comprising:

at least one memory for storing computer-executable instructions; and

at least one processor configured to execute the stored instructions to:

identify a first individual with an unknown genetic disorder by analysis of first electronic data reflective of first values corresponding to pixels of an external soft tissue image of the first

individual, wherein the first values correspond to relationships between at least one group of pixels in the external soft tissue image of the first individual;

identify a second individual with a known genetic disorder by analysis of second electronic data reflective second values corresponding to second pixels of an external soft tissue image of the second individual, wherein the second values correspond to relationships between at least one group of pixels in the external soft tissue image of the second individual;

compare at least some of the analyzed data of the first individual with at least some of the analyzed data of the second individual; and

determine that the first individual is likely to share the known genetic disorder of the second individual based on the comparison.

23. The system of claim 22, wherein determining that the first individual is likely to share the known genetic disorder comprises determining that the unknown genetic disorder is likely within a class defined by a genomic pathway that contains the known genetic disorder.

24. The system of claim 23, wherein the class defined by the genomic pathway comprises a number of genetic disorders that are caused by variants within one or more of the same genes.

25. An electronic system for performing image processing in connection with phenotypic analysis, the electronic system comprising:

at least one memory for storing computer-executable instructions; and

at least one processor configured to execute the stored instructions to:

receive electronic numerical information corresponding to pixels reflective of at least one external soft tissue image of an individual;

access geographically dispersed genetic information stored in a database, wherein the geographically dispersed genetic information includes numerical data that correlates anomalies in pixels in soft tissue images of a plurality of geographically dispersed individuals to specific genes or to specific genetic variants;

compare the electronic numerical information for the individual with the numerical data of the geographically dispersed genetic information stored in a database, to determine at least a likelihood that the individual has at least one pathogenic genetic variant; and

prioritize, based on the comparison, one or more genetic variants according to a likelihood of pathogenicity.

26. The system of claim 25, wherein prioritizing includes assigning the one or more genetic variants to at least one pathogenicity class.

27. The system of claim 25, wherein the at least one processor is further configured to access phenotypic data associated with the individual and phenotypic data associated with the plurality of geographically dispersed individuals, and wherein the prioritizing is further based on a comparison of the phenotypic data of the individual with the phenotypic data of the geographically dispersed individuals.

28. The system of claim 27, wherein the phenotypic data associated with the individual and the phenotypic data associated with the plurality of geographically dispersed individuals are textual.

29. The system of claim 27, wherein the phenotypic data associated with the individual is received from the individual.

30. The system of claim 27, wherein the phenotypic data associated with the plurality of geographically dispersed individuals is received from the plurality of geographically dispersed individuals.

31. The system of claim 25, wherein the geographically dispersed genetic information includes genetic test information.

32. The system of claim 31 , wherein the genetic test information includes one or more medical professional annotations.

33. The system of claim 32, wherein the one or more professional annotations includes words coding for a phenotypic feature.

34. The system of claim 33, wherein the phenotypic feature includes a description of a medical professional observation of an anatomical feature.

35. The system of claim 25, wherein the at least one external soft tissue image of the individual is two-dimensional.

36. The system of claim 25, wherein the electronic numerical information comprises de-identified representations of the at least one external soft tissue image.

37. The system of claim 36, wherein de-identification is performed using one or more convolutional neural networks.

38. A computer-implemented method for performing image processing in connection with phenotypic analysis, the method comprising:

receiving, with processing circuitry, electronic numerical information corresponding to pixels reflective of at least one external soft tissue image of an individual;

accessing geographically dispersed genetic information stored in a database, wherein the geographically dispersed genetic information includes numerical data that correlates anomalies in pixels in soft tissue images of a plurality of geographically dispersed individuals to specific genes or to specific genetic variants;

comparing, with the processing circuitry, the electronic numerical information for the individual with the numerical data of the geographically dispersed genetic information stored in a database, to determine at least a likelihood that the individual has at least one pathogenic genetic variant; and

prioritizing, with the processing circuitry, based on the comparison, one or more genetic variants according to a likelihood of pathogenicity.

39. The method of claim 38, further comprising:

accessing phenotypic data associated with the individual and phenotypic data associated with the plurality of geographically dispersed individuals,

wherein the prioritizing is further based on a comparison of the textual phenotypic data of the individual with the phenotypic data of the geographically dispersed individuals.

40. The method of claim 39, wherein the phenotypic data associated with the individual is received from the individual.

41. The method of claim 39, wherein the phenotypic data associated with the plurality of geographically dispersed individuals is received from the plurality od geographically dispersed individuals.

42. The method of claim 38, wherein the geographically dispersed genetic information includes annotated genetic test information.

43. The method of claim 42, wherein the annotations include words coding for a phenotypic feature.

44. The method of claim 38,

wherein the electronic numerical information comprises de-identified representations of the at least one external soft tissue image, and

the method further comprises de-identifying the at least one external soft tissue image using one or more convolutional neural networks.

45. A non-transitory, computer-readable medium storing instructions for performing image processing in connection with phenotypic analysis, the instructions causing one or more processors to: receive electronic numerical information corresponding to pixels reflective of at least one external soft tissue image of an individual;

access geographically dispersed genetic information stored in a database, wherein the geographically dispersed genetic information includes numerical data that correlates anomalies in pixels in soft tissue images of a plurality of geographically dispersed individuals to specific genes or to specific genetic variants;

compare the electronic numerical information for the individual with the numerical data of the geographically dispersed genetic information stored in a database, to determine at least a likelihood that the individual has at least one pathogenic genetic variant; and

prioritize, based on the comparison, one or more genetic variants according to a likelihood of pathogenicity.