Communication generation using sparse indicators and sensor data

A system for generating communications based on variant information and sensor data, comprising:

• one or more hardware processors;
• and
• a non-transitory computer readable storage medium in data communication with the one or more hardware processors, the non-transitory computer readable storage medium comprising instructions that, when executed by the one or more hardware processors, cause the one or more hardware processors to perform operations including:
• obtain, at the one or more hardware processors, genetic-variant data corresponding to one or more variants associated with a client, wherein each of the one or more variants corresponds to an instance of one or more bases positioned at one or more first positions in a first genetic sequence differ from corresponding one or more bases positioned in a reference genetic sequence, wherein the first genetic sequence is a genetic sequence of the client;
• predict a reliability of the genetic-variant data by performing a comparison of the genetic-variant data based on different labs, different devices, or different time periods associated with data collection;
• obtain other data that include at least sensor data providing an indication of one or more characteristics of the client, current quality of the client, behavior of the client, or one or more characteristics of a current or past environment of the client;
• process, based on the reliability of the genetic-variant data, the genetic-variant data and the other data to generate a disease-risk metric corresponding to a predicted risk of the client developing a particular disease;
• generate a communication indicative of the disease-risk metric;
• and
• availing the communication to a remote device.

A computer-program product tangibly embodied in a non-transitory machine-readable storage medium, including instructions configured to cause one or more data processors to perform a set of operations including:

• accessing genetic-variant data corresponding to one or more variants associated with a client, wherein each of the one or more variants corresponds to an instance of one or more bases positioned at one or more first positions in a first genetic sequence differ from corresponding one or more bases positioned in a reference genetic sequence, wherein the first genetic sequence is a genetic sequence of the client;
• predicting a reliability of the genetic-variant data by transforming an input data set using an artificial intelligence technique, wherein the input data set indicates a laboratory, device, or a collection time period associated with the genetic-variant data;
• obtaining other data that include at least sensor data;
• processing, based on the reliability of the genetic-variant data, the genetic-variant data and the other data to generate a disease-risk metric corresponding to a predicted risk of the client developing a particular disease;
• generating a communication indicative of the disease-risk metric;
• and
• availing the communication to a remote device.