Diagnostic lab-on-a-chip device

A diagnostic hub located in a toilet, consisting of:

• one or more computer processors;
• and
• a non-transitory computer-readable storage medium storing computer instructions, which, when executed by the one or more computer processors, cause the diagnostic hub to:
• receive, by a wireless transceiver, a wireless signal from a mobile device;
• determine a user identification and that the mobile device is proximate to the toilet based on the wireless signal;
• determine a geolocation by at least one of:
• analyzing location signals received by a geolocation receiver;
• or
• analyzing location information embedded in the wireless signal;
• receive sensor data generated by a plurality of biometric sensors and environmental sensors communicably coupled to the diagnostic hub;
• intake a mixture of water and at least one of urine or feces from the toilet into an intake chamber through an inlet line or one or more openings in a housing of the diagnostic hub;
• perform an analysis, by a lab-on-a-chip, of the mixture by:
• biosensing one or more micro ribonucleic acid (miRNA) biomarkers in the mixture using one or more biosensors;
• and
• performing a biochemical assay to produce one or more measurements of:
• cellular processes or metabolic reactions;
• and
• substances or functional activity of biomolecules;
• extract a feature vector from the one or more miRNA biomarkers and the one or more measurements;
• determine, from the feature vector, one of:
• a diagnosis of one or more diseases or medical conditions of a user;
• a likelihood that the user will develop the one or more diseases or medical conditions;
• or
• a change in severity of the one or more diseases or medical conditions in the user;
• correlate the analysis to the sensor data;
• and
• transmit, by the wireless transceiver, the correlated analysis to the mobile device or a cloud server, wherein the correlated analysis is tagged by the user identification and the geolocation.

A non-transitory computer-readable storage medium storing computer instructions, which, when executed by one or more computer processors, cause the one or more computer processors to:

• receive, by a wireless transceiver, a wireless signal from a mobile device;
• determine a user identification and that the mobile device is proximate to a toilet based on the wireless signal;
• determine a geolocation by at least one of:
• analyzing location signals received by a geolocation receiver;
• or
• analyzing location information embedded in the wireless signal;
• receive sensor data generated by a plurality of biometric sensors and environmental sensors communicably coupled to a diagnostic hub;
• intake a mixture of water and at least one of urine or feces from the toilet into an intake chamber through an inlet line or one or more openings in a housing of the diagnostic hub;
• biosense, by a lab-on-a-chip, one or more micro ribonucleic acid (miRNA) biomarkers in the mixture using one or more biosensors;
• perform a biochemical assay on a fluid volume of the mixture, using a biochemical reagent, to produce one or more measurements of:
• cellular processes or metabolic reactions;
• and substances or functional activity of biomolecules;
• perform an analysis, by the one or more computer processors implemented in the diagnostic hub, by:
• extracting a feature vector from the one or more miRNA biomarkers and the one or more measurements;
• and
• determining, using at least one machine learning model, from the feature vector, at least one of:
• a diagnosis of one or more diseases or medical conditions of a user;
• a likelihood that the user will develop the one or more diseases or medical conditions;
• a likelihood that the user will develop a more severe or more mild form of one more diseases or medical conditions;
• pre-existing conditions or risk factors for other diseases or medical conditions;
• or
• a change in severity of the one or more diseases or medical conditions in the user;
• correlate the analysis to the sensor data;
• and transmit, by the wireless transceiver, the correlated analysis to the mobile device or a cloud server, wherein the correlated analysis is tagged by the user identification and the geolocation.