Abstract: Methods, systems, and apparatus, including computer-readable media, for machine learning in a multi-tenant data sharing platform. In some implementations, a server system provides a multi-tenant data sharing platform configured to selectively use stored data collected for different tenant organizations according to policy data for the respective tenant organizations. A request from one organization is received to perform a machine learning task involving a data set of a different tenant organization. The server system uses stored policy data to determine an applicable data policy, and based on the determination, the server system performs the machine learning task and provides the results of the machine learning task.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer-storage media, for machine learning to select digital therapeutics. In some implementations, a machine learning model is trained to generate scores that indicate the level of applicability of different digital therapeutics based on input data for a person. A computer system monitors health of an individual using surveys and sensor measurements. The computer system identifies one or more signs or symptoms of a disease based on the monitoring data for the individual. The computer system uses output of the machine learning model to select a digital therapeutic intervention for the user. The computer system cause one or more devices to deliver the selected digital therapeutic intervention to the individual, monitor a response of the individual to the selected digital therapeutic intervention, and adjust characteristics of the digital therapeutic intervention based on the monitored response.

Abstract: Systems, methods, and apparatus, including computer-readable media for managing and adapting monitoring programs. In some implementations, a system accesses data describing a monitoring program that involves collecting data over a period of time from a monitoring group comprising geographically distributed devices. The system classifies the devices in the monitoring group into different groups for the categories based on the attributes associated with the devices. The system monitoring performance of the devices in the different groups and determines a performance score for each group. The system adjusts administration of the monitoring program based on the performance scores, including performing one or more actions to improve diversity in the monitoring group.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for improving distributed monitoring using different groups of remote devices. In some implementations, a system communicates with a set of remote devices involved in a first monitoring program that involves collection of data from the remote devices over a communication network. The system identifies a pattern or similarity among monitoring data collected from a subset of the remote devices involved in the first monitoring program. The system determines that the identified pattern or similarity satisfies one or more criteria for initiating additional monitoring. In response, the system determines parameters specifying second types of data to collect in a second monitoring program. The system configures one or more devices to perform monitoring for the second monitoring program including acquiring data for the second types of data and providing the acquired data to a server over the communication network.

Abstract: Systems and methods for using a reconfigurable multi-manager observer system to identify markers are provided. The system allows for easy collaboration among users of the system and with subjects. Systems and methods may comprise receiving subject data, selecting predictor and outcome variable classes based on the data, generating a predictor score based on the data and a predictor rule, generating an outcome score based on the data and an outcome rule, generating a marker score based on the predictor score and a marker rule, generating a marker metric based on the outcome score, the marker score, and a marker relationship, and, optionally, taking an action based on the predictor score, the outcome score, the marker score, or the marker metric.

Abstract: In some implementations, a system includes a database comprising program data for each of a plurality of programs that involve monitoring using remote devices. The system includes a server system configured to selectively distribute the configuration data for the respective programs to remote devices over a communication network and monitor incoming data received from the remote devices over the communication network to determine changes to programs active for the remote devices. The server system can be configured to collect, from the respective remote devices, monitoring data that is generated by the programs active for the remote devices and is provided over the communication network. The server system can compare the collected monitoring data with reference levels, select one or more program changes, and distribute, to various remote devices, data indicating appropriate program changes for the remote devices.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for assessing and adjusting the composition of groups for monitoring programs. In some implementations, a computer system determines a target level of diversity for a monitoring program based on a composition of a reference group. The system determines a group level of diversity for a group based on the composition of the group, wherein the group comprises at least one of candidates or participants for the monitoring program. The system determines that the group level of diversity does not provide the target level of diversity, and in response, selects one or more actions that are configured to adjust the composition of the group to achieve the target level of diversity in the group. The system provides output data that indicates the selected one or more actions to adjust the composition of the group toward the target level of diversity for the group.

Abstract: A system and method for an adjustable bio-stream self-selecting system. Through a plethora of inputs, the system associates therapeutic recipes and associated biomarker in a personalized approach to recommending an individual to a specific therapeutic program. Therapeutic programs operate in accordance with personalized inputs suggested by the user and through digital markers and biomarkers, which trigger new recommendations by “knowing” the individual. Each bio-stream contains information utilized within these biomarkers to trigger additional therapy recommendations. Because of the complexity of the plurality of inputs, these biomarkers are managed in a way that enables low latency detections, low bandwidth needs, low processing needs, and less battery needs. The pre-processing of these biomarkers helps additional therapy management and precision medicine across larger global population needs of the system.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for using machine learning to generate precision predictions of readiness. In some implementations, a database is accessed to obtain status data that indicates activities or attributes of a subject. A set of feature scores is derived from the status data for the subject, the set of feature scores including values indicative of attributes or activities of the subject. The set of feature scores to one or more models that have been configured to predict readiness of subjects to satisfy one or more readiness criteria. The one or models can be models configured using machine learning training. Based on processing performed using the one or more machine learning models and the set of feature scores, a prediction regarding the subject's ability to achieve readiness to satisfy the one or more readiness criteria is generated.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for using machine learning to improve processes for achieving readiness. In some implementations, a database is accessed to obtain status data that indicates activities or attributes of a subject. One or more readiness scores indicating a level of capability of the subject to satisfy one or more readiness criteria are generated. Data is accessed indicating multiple candidate actions for improving capability of the subject to satisfy one or more readiness criteria. A subset of the candidate actions for the subject are selected based on the one or more readiness scores generated using the one or more models. Output is provided to cause one or more of the actions in the selected subset to be performed or cause an indication one or more of the actions in the selected subset to be presented on a user interface.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer-storage media, for collecting monitoring data and predicting outcomes for communities. In some implementations, monitoring data is received, including location tracking data that indicates locations visited by individuals in a community. Community data for the community that describes characteristics of the community and a geographic region associated with the community is received. One or more predictive models are used to evaluate regions for potential for transmission of a disease based on behavior patterns of individuals in the community. The one or more predictive models can be models trained based on training data describing a plurality of different communities and behavior patterns and disease outcomes of individuals in the different communities over time.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer-storage media, for context-based evaluation to enhance the relevance and usefulness of computer system output. In some implementations, a computer system is configured to customize its interactions for a particular situation or user. The system can obtain context information and evaluate the relevance and usefulness of potential outputs and actions with respect to the context indicated by the context information. For example, the system can vary the type and format of output information based on information that describes the intended recipient and the situation of the recipient. The system can take into account many different factors in its evaluation, including timing, user preferences, user history, user classification, impact or effect of the system's decisions on users, and more.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for using machine learning to improve processes for achieving readiness. In some implementations, a database is accessed to obtain status data that indicates activities or attributes of a subject. One or more readiness scores indicating a level of capability of the subject to satisfy one or more readiness criteria are generated. Data is accessed indicating multiple candidate actions for improving capability of the subject to satisfy one or more readiness criteria. A subset of the candidate actions for the subject are selected based on the one or more readiness scores generated using the one or more models. Output is provided to cause one or more of the actions in the selected subset to be performed or cause an indication one or more of the actions in the selected subset to be presented on a user interface.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for using machine learning to generate precision predictions of readiness. In some implementations, a database is accessed to obtain status data that indicates activities or attributes of a subject. A set of feature scores is derived from the status data for the subject, the set of feature scores including values indicative of attributes or activities of the subject. The set of feature scores to one or more models that have been configured to predict readiness of subjects to satisfy one or more readiness criteria. The one or models can be models configured using machine learning training. Based on processing performed using the one or more machine learning models and the set of feature scores, a prediction regarding the subject's ability to achieve readiness to satisfy the one or more readiness criteria is generated.

Abstract: Methods, systems, and apparatus, including computer-readable media, for a hierarchical multi-tenant data access platforms. In some implementations, the a server system stores data collected through a multi-tenant data access platform configured to collect data for each of multiple tenant organizations and to selectively make the collected data available according to policies associated with the respective tenant organizations. The server system receives a request associated with a user, and the server system generates and provides a response according to the organization hierarchy data and policy data for the unit of the organization that has data that would be used in generating the response to the request.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for monitoring technology usage and performance. In some implementations, use of a technology item by one or more individuals assigned to use the technology item is monitored. Based on the monitoring, usage data that indicates usage of the technology item is generated. One or more criteria for evaluating the usage of the technology item by the one or more individuals is identified. It is determined whether usage data satisfies the one or more criteria. A system performs at least one of (i) evaluating an alternative technology item for the one or more individuals, or (ii) providing, for display on a user interface, output data indicating whether the usage data satisfies the one or more criteria.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer-storage media, for predictive analysis and interventions to limit disease exposure. In some implementations, user data indicating a prospective action of a user of a mobile device is received. Content is provided to cause the mobile device associated with the user to present a prompt for user input regarding the prospective action of the user. Potential future exposure of the user to a disease is evaluated based on response data indicating a response to the prompt. A disease exposure prevention option for the user is selected or customized for the user based on at least one of the user data or the response data. Content is provided to cause the mobile device associated with the user to present the disease exposure prevention option.

Abstract: Systems and methods for personalized digital goal setting and intervention are provided. Embodiments of the system allow for effective management and implementation of interventions to change behaviors or health statuses of individuals or groups. Systems and methods may include setting a measurement goal relating to a behavior or a health status and generating a marker based on the measurement goal, receiving sensor data, determining that at least one of the measurement goal or the marker is satisfied, and executing a triggering action. The triggering action may include at least one of controlling access to a user device, controlling access to an application stored on a user device, controlling access of a user device to a network, controlling access of a user device to a website, displaying a notification on the user device, or transmitting a command to a remote device, including an instruction to control access to a physical space.

Abstract: Systems and methods for personalized digital goal setting and intervention are provided. Embodiments of the system allow for effective management and implementation of interventions to change behaviors or health statuses of individuals or groups. Systems and methods may include setting a measurement goal relating to a behavior or a health status and generating a marker based on the measurement goal, receiving sensor data, determining that at least one of the measurement goal or the marker is satisfied, and executing a triggering action. The triggering action may include at least one of controlling access to a user device, controlling access to an application stored on a user device, controlling access of a user device to a network, controlling access of a user device to a website, displaying a notification on the user device, or transmitting a command to a remote device, including an instruction to control access to a physical space.

Abstract: The systems and methods of the invention provide a network querying or content system which drives high relevance question sets or content to users and presents it in the optimal template to ensure user interaction. In accord with at least one aspect, the system assesses the context (of a user) by interpreting the optimal template based on personality mapping of the user and relevancy mapping of the query or content. In a technically efficient manner, the system employs client-based managers and builders to select, supplement, or build user profiles and user interface templates to optimize queries or content based on a user's present profile. The systems and methods of the invention perform processing, in a technically efficient manner, to assess question or content set interaction and relevancy to generate targeted question sets or content that encourage overall user health and wellness.