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AI Biotech/Diagnostics: Cardio

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Patent US10325673


Issued 2019-06-18

Deep Transcriptomic Markers Of Human Biological Aging And Methods Of Determining A Biological Aging Clock

A method of creating a biological aging clock for a subject can include: (a) receiving a transcriptome signature derived from a tissue or organ of the subject; (b) creating input vectors based on the transcriptome signature; (c) inputting the input vectors into a machine learning platform; (d) generating a predicted biological aging clock of the tissue or organ based on the input vectors by the machine learning platform, wherein the biological aging clock is specific to the tissue or organ; and (e) preparing a report that includes the biological aging clock that identifies a predicted biological age of the tissue or organ.



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2 Independent Claims

  • 1. A method of creating a biological aging clock for a subject, the method comprising: (a) receiving a transcriptome signature derived from a tissue or organ of the subject; (b) creating input vectors based on the transcriptome signature; (c) inputting the input vectors into a machine learning platform; (d) generating a predicted biological aging clock of the tissue or organ based on the input vectors by the machine learning platform, wherein the biological aging clock is specific to the tissue or organ; and (e) preparing a report that includes the biological aging clock that identifies a predicted biological age of the tissue or organ.

  • 16. A computer program product comprising a tangible, non-transitory computer readable medium having a computer readable program code stored thereon, the code being executable by a processor to perform a method for biological aging clock for a patient, the method comprising: (a) receiving a transcriptome signature derived from a tissue or organ of the subject; (b) creating input vectors based on the transcriptome signature; (c) inputting the input vectors into a machine learning platform; (d) generating a predicted biological aging clock of the tissue or organ based on the input vectors by the machine learning platform, wherein the biological aging clock is specific to the tissue or organ; and (e) preparing a report that includes the biological aging clock that identifies a predicted biological age of the tissue or organ.