Abstract: Aspects of the present disclosure are directed to systems, methods, and computer readable media for configuring generation of digital therapeutic content for provision. A computing system may identify content to be provided via a network. The computing system may apply the content to a machine learning (ML) model to generate an output. The computing system may determine, from the output, a compliance status of the content. The computing system may identify, based on applying the ML model, at least a subsection of the content to be modified. The computing system may identify the content to be modified responsive to determining the compliance status of the content.

Abstract: Aspects of the present disclosure are directed to systems, methods, and computer readable media for executing actions for events associated with use of applications. A computing system can identify data associated with an application to be evaluated for at least one of a plurality of events associated with a use of the application. The computing system can determine, based on applying the free text to a machine learning (ML) architecture, a value indicating a likelihood of occurrence of an event associated with the use of the application. The computing system can provide to a generative ML model, a model input based on the free data and the value. The computing system can execute an action corresponding to characterizing the event.

Abstract: Aspects of the present disclosure are directed to systems, methods, and computer readable media for generating messages targeted to address conditions in users. A computing system may identify (i) a condition of a user to be addressed and (ii) one or more parameters defining messages to be presented via an application towards achieving an endpoint associated with the condition for the user. The computing system may generate a prompt using the condition and the one or more parameters in accordance with a template. The computing system may apply the prompt to a generative model to output a message identifying at least one activity toward achieving the endpoint. The generative model may be trained using a corpus. The computing system may provide, the message for presentation to prompt the user to perform the activity via the application towards achieving the endpoint to address the condition.

Abstract: Provided herein are systems and methods for methods for detecting expected reductions of interactions across sessions. A computing system can identify event data identifying interactions by a user with a first session for digital therapeutic content to address a condition. The computing system can apply the event data to a machine learning (ML) model. The computing system can generate a likelihood of the user interacting with a second session for digital therapeutic content based on applying the event data to the ML model. The computing system can detect an expected reduction in interactions by the user with the second session, responsive to the likelihood of the user not satisfying a threshold. The computing system can provide an output for the user based on detecting the expected reduction in interactions. In this manner, the efficacy of the medication that user is concurrently taking to address the condition may be improved.

Abstract: Aspects of the present disclosure are directed to systems, methods, and computer readable media for executing actions for events associated with use of applications. A computing system can identify data associated with an application to be evaluated for at least one of a plurality of events associated with a use of the application. The computing system can determine, based on applying the free text to a machine learning (ML) architecture, a value indicating a likelihood of occurrence of an event associated with the use of the application. The computing system can provide to a generative ML model, a model input based on the free data and the value. The computing system can execute an action corresponding to characterizing the event.

Abstract: Aspects of the present disclosure are directed to systems, methods, and computer readable media for configuring generation of digital therapeutic content for provision. A computing system may identify content to be provided via a network. The computing system may apply the content to a machine learning (ML) model to generate an output. The computing system may determine, from the output, a compliance status of the content. The computing system may identify, based on applying the ML model, at least a subsection of the content to be modified. The computing system may identify the content to be modified responsive to determining the compliance status of the content.

Abstract: Aspects of the present disclosure are directed to systems and methods of dynamically generating individualized or personalized times for providing messages over networked environments. The computing system may obtain, for a user device, an event dataset identifying a plurality of interaction times corresponding to a plurality of interactions over an instant time window by a user with an application on the user device to address a condition of the user. The computing system may apply the event dataset to a machine learning (ML) model. The computing system may generate based on applying the event dataset to the ML model, a defined time at which a message is to be provided to the user device during a subsequent time window. The computing system may provide for presentation on the user device to address the condition of the user, the message in accordance with the defined time.

Abstract: Provided herein are systems and methods of managing access to data associated with trials for digital therapeutics on participants. One or more processors can maintain a data lake for a plurality of phases associated with a trial for a digital therapeutic on participants. The data lake may a plurality of datasets corresponding to at least one of the plurality of phases. The one or more processors can receive, from a user device, a request corresponding with at least one of a participant or group of participants, an endpoint, and a phase of the plurality of phases corresponding with accessing the plurality of datasets. The one or more processors can select a corresponding portion of the plurality of datasets based on the request to provide the user device.

Abstract: Provided herein are systems and methods for methods for detecting expected reductions of interactions across sessions. A computing system can identify event data identifying interactions by a user with a first session for digital therapeutic content to address a condition. The computing system can apply the event data to a machine learning (ML) model. The computing system can generate a likelihood of the user interacting with a second session for digital therapeutic content based on applying the event data to the ML model. The computing system can detect an expected reduction in interactions by the user with the second session, responsive to the likelihood of the user not satisfying a threshold. The computing system can provide an output for the user based on detecting the expected reduction in interactions. In this manner, the efficacy of the medication that user is concurrently taking to address the condition may be improved.

Abstract: Provided herein are systems and methods of managing access to data associated with trials for digital therapeutics on participants. A server can maintain a data storage for a plurality of phases associated with a trial for a digital therapeutic on participants. The data storage may include (i) a first portion of a plurality of datasets from the plurality of participants from one or more of the plurality of phases of the trial, and (ii) a second portion of the plurality of datasets from the digital therapeutics in at least one of the plurality of phases of the trial. The server can receive from a user device, a request identifying a phase of the plurality of phases for which the plurality of datasets is to be accessed. The server can select a corresponding portion of the plurality of datasets based on the request to provide the user device.

Abstract: Aspects of the present disclosure are directed to systems, methods, and computer readable media for configuring generation of digital therapeutic content for provision. A computing system may identify content to be provided via a network. The computing system may apply the content to a machine learning (ML) model to generate an output. The computing system may determine, from the output, a compliance status of the content. The computing system may identify, based on applying the ML model, at least a subsection of the content to be modified. The computing system may identify the content to be modified responsive to determining the compliance status of the content.

Abstract: Provided herein are systems and methods for providing instructions for speech based on speech classifications of verbal communications from users. Ae computing system can generate speech characteristics for a first verbal communication using a first audio sample from a user. The computing system can determine, from a plurality of speech classifications, a first speech classification for the first verbal communication based on the speech characteristics. The computing system can select, from a plurality of actions, an action comprising modifying one or more of the speech characteristics to define an utterance for the user based on the first speech classification. The computing system can provide an instruction presenting a message to prompt the user to perform the utterance defined by the action selected from the plurality of actions. The efficacy of the medication that the user is taking to address the condition may be increased.

Abstract: Aspects of the present disclosure are directed to systems, methods, and computer readable media for regulating digital therapeutic content for provision. A computing system may identify a digital therapeutic content to be provided via a network. The computing system may apply the digital therapeutic content to a machine learning (ML) model having a set of weights. The computing system may determine, from applying the digital therapeutic content to the ML model, an indication as of one of compliance or non-compliance. The computing system may store, using one or more data structures, an association between the digital therapeutic content and the indication used to control provision of the digital therapeutic content via the network, by (i) restricting the digital therapeutic content from provision responsive to determining the indication of non-compliance and (ii) permitting the digital therapeutic content to be provided responsive to determining the indication of compliance.

Abstract: Aspects of the present disclosure are directed to systems, methods, and computer readable media for regulating digital therapeutic content for provision. A computing system may identify a digital therapeutic content to be provided via a network. The computing system may apply the digital therapeutic content to a machine learning (ML) model having a set of weights. The computing system may determine, from applying the digital therapeutic content to the ML model, an indication as of one of compliance or non-compliance. The computing system may store, using one or more data structures, an association between the digital therapeutic content and the indication used to control provision of the digital therapeutic content via the network, by (i) restricting the digital therapeutic content from provision responsive to determining the indication of non-compliance and (ii) permitting the digital therapeutic content to be provided responsive to determining the indication of compliance.

Abstract: Aspects of the present disclosure are directed to systems, methods, and computer readable media for regulating digital therapeutic content for provision. A computing system may identify a digital therapeutic content to be provided via a network. The computing system may apply the digital therapeutic content to a machine learning (ML) model having a set of weights. The computing system may determine, from applying the digital therapeutic content to the ML model, an indication as of one of compliance or non-compliance. The computing system may store, using one or more data structures, an association between the digital therapeutic content and the indication used to control provision of the digital therapeutic content via the network, by (i) restricting the digital therapeutic content from provision responsive to determining the indication of non-compliance and (ii) permitting the digital therapeutic content to be provided responsive to determining the indication of compliance.

Abstract: Aspects of the present disclosure are directed to systems, methods, and computer readable media for configuring generation of digital therapeutic content for provision. The system can receive a text input including one or more parameters identifying an audience and at least one domain. The system can identify content items generated by corresponding generative transformer models each using a prompt created based on the text input. The system can select, from a set of risk models for the domains, at least one risk model corresponding to the at least one domain. The system can apply the at least one risk model to each content item of the set of content items to determine a risk score. The system can select a content item based on the risk score of the content item. The system can present the content item including the respective digital therapeutic content.

Abstract: Aspects of the present disclosure are directed to systems, methods, and computer readable media for regulating digital therapeutic content for provision. A computing system may identify a digital therapeutic content to be provided via a network. The computing system may apply the digital therapeutic content to a machine learning (ML) model having a set of weights. The computing system may determine, from applying the digital therapeutic content to the ML model, an indication as of one of compliance or non-compliance. The computing system may store, using one or more data structures, an association between the digital therapeutic content and the indication used to control provision of the digital therapeutic content via the network, by (i) restricting the digital therapeutic content from provision responsive to determining the indication of non-compliance and (ii) permitting the digital therapeutic content to be provided responsive to determining the indication of compliance.

Abstract: Aspects of the present disclosure are directed to systems, methods, and computer readable media for executing actions for events associated with use of applications. A computing system can identify free text associated with an application to be evaluated for at least one of a plurality of events associated with a use of the application. The computing system can apply the free text to a machine learning (ML) architecture. The computing system can determine, based on applying the free text to the ML architecture, a value indicating a likelihood of occurrence of an event associated with the use of the application. The computing system can provide to a generative ML model, a model input based on the free text and the value, to obtain data for an electronic document characterizing the event. The computing system can execute an action using the data for the electronic document.

Abstract: Aspects of the present disclosure are directed to systems, methods, and computer readable media for generating messages targeted to address conditions in users. A computing system may identify (i) a condition of a user to be addressed and (ii) one or more parameters defining messages to be presented via an application towards achieving an endpoint associated with the condition for the user. The computing system may generate a prompt using the condition and the one or more parameters in accordance with a template. The computing system may apply the prompt to a generative model to output a message identifying at least one activity toward achieving the endpoint. The generative model may be trained using a corpus. The computing system may provide, the message for presentation to prompt the user to perform the activity via the application towards achieving the endpoint to address the condition.

Abstract: Provided herein are systems and methods of managing access to data associated with trials for digital therapeutics on participants. A server can maintain a data storage for a plurality of phases associated with a trial for a digital therapeutic on participants. The data storage may include (i) a first portion of a plurality of datasets from the plurality of participants from one or more of the plurality of phases of the trial, and (ii) a second portion of the plurality of datasets from the digital therapeutics in at least one of the plurality of phases of the trial. The server can receive from a user device, a request identifying a phase of the plurality of phases for which the plurality of datasets is to be accessed. The server can select a corresponding portion of the plurality of datasets based on the request to provide the user device.