Patent US10660522 AI Biotech/Diagnostics: Cardio

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I2dx Inc.

Patent US10660522

Issued 2020-05-26

Electronic Delivery Of Information In Personalized Medicine

According to an aspect of an embodiment, a social network system for electronic delivery of information in personalized health care, may include capturing one or more data streams where each of the data streams relates to health care of a patient. The system may further include integrating the data streams to generate integrated diagnostic data and analyzing the integrated diagnostic data to generate analyzed diagnostic data. The system may further include curating the analyzed diagnostic data and generating an integrated report for presentation to a physician of the patient based on the curated analyzed diagnostic data.

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3 Independent Claims

1. A system for electronic delivery of information in personalized health care, the system comprising: one or more servers configured to host a healthcare social network particular to providing personalized health care for an individual patient, the one or more servers configured to: accept the individual patient as a new patient in the healthcare social network, communicate with testing equipment coupled with the healthcare social network, the testing equipment configured to provide signal data that are generated by diagnostic testing performed on the individual patient using the testing equipment, and add content data for the individual patient in the healthcare social network, the content data including the signal data; and a data analytics unit networked to the one or more servers and configured to: receive data signals over the healthcare social network concerning the personalized health care of the individual patient, the received data signals at least in part derived from the content data of the individual patient shared over the healthcare social network, analyze the data signals to determine a diagnostic profile for the individual patient, generate a presentation of the diagnostic profile with contextual medical information, flag potential calculation errors due to hardware in the data analytics unit by running random check calculations on external reference datasets and comparing the random check calculations against a respective reference value, and correct numerical instabilities of analytics calculations performed by the data analytics unit by performing a recalculation at a later time or on different hardware based on the random check calculations.
13. A computer-implemented method of delivering information-enabled personalized health care with respect to early Alzheimer's disease in a clinical, non-research setting, the computer-implemented method comprising: provisioning, using one or more servers, a healthcare social network particular to providing personalized health care for an individual patient, the healthcare social network configured to: accept the individual patient as a new patient in the healthcare social network, add content data for the individual patient, the content data including one or more physical measurements from diagnostic testing performed on the individual patient using testing equipment coupled with the healthcare social network, specify recipients within the healthcare social network particular to the individual patient for delivery of the content data, and provide a secure interface for multiple human participants particular to the individual patient to exchange bidirectional secure correspondence within the healthcare social network regarding the personalized health care of the individual patient and transfer the content data there between based on permissions within the healthcare social network, capturing one or more data streams, each of the data streams related to health care of the individual patient provided by one or more of the multiple human participants, including the correspondence between the multiple human participants, wherein one or more of the data streams include the content data that includes results from the diagnostic testing of the individual patient; analyzing, using one or more processors, the one or more data streams to generate a diagnostic profile for the individual patient; flagging potential calculation errors, due to hardware in the one or more processors analyzing the one or more data streams, by running random check calculations on external reference datasets and comparing the random check calculations against a respective reference value; correct numerical instabilities of analytics calculations performed by the one or more processors analyzing the one or more data streams by performing a recalculation at a later time or on different hardware based on the random check calculations; curating, using the one or more processors, the diagnostic profile by presenting the diagnostic profile with contextual medical information; and generating, using the one or more processors, an integrated report for presentation to a physician of the individual patient using the curated diagnostic profile, the integrated report for providing a personalized therapy for the individual patient with respect to the curated diagnostic profile.
21. A computing system for advanced, automated analytics of data on a personalized health care social network, the system comprising: one or more servers configured to host a healthcare social network particular to providing personalized health care for an individual patient, the healthcare social network configured to: accept the individual patient as a new patient in the healthcare social network, add content data for the individual patient, specify recipients within the healthcare social network particular to the individual patient for delivery of the content data, and provide a secure interface for multiple human participants particular to the individual patient to exchange bidirectional secure correspondence within the healthcare social network regarding the personalized health care of the individual patient and transfer the content data there between, the correspondence including communications regarding a particular treatment for the individual patient; a data anonymizer unit networked to the one or more servers and configured to receive the content data associated with the personalized health care of the individual patient through the healthcare social network and to remove at least a portion of patient identifying information from the received content data to generate first anonymized data; a data analytics unit networked to the data anonymizer unit and configured to: analyze the first anonymized data to generate analytic information with respect to the individual patient, the analysis of the first anonymized data performed based on the analytic information including at least one diagnostic marker for the individual patient, flag potential calculation errors due to hardware in the data analytics unit by running random check calculations on external reference datasets and comparing the random check calculations against a respective reference value, and correct numerical instabilities of analytics calculations performed by the data analytics unit by performing a recalculation at a later time or on different hardware based on the random check calculations; and an augmented reality (AR) user interface device networked to the data analytics unit and configured to provide computer instructions for presentation to a AR user interface that is configured to present information including the analytic information generated by the data analytics unit.