Abstract: A system and method are disclosed for predicting short term health outcomes based on data collected by a wearable device such as an activity tracker or a smart watch. Artificial Intelligence (AI) algorithms are configured to process an input vector that includes monitored parameter data collected by the wearable device as well as embedding data obtained from health records corresponding to a user account registered to the wearable device. In particular, a framework is defined that includes a random forest model configured to classify a user based on the monitored parameter data and embedding data. Based on a positive health outcome classification, a minimum value is assigned to a health index value for the user or, based on a negative health outcome classification, a gradient boosting machine is configured to generate the health index value. Various operations can be performed based on the assigned health index value for the user.

Abstract: A system comprising a first user device is provided. The first user device is configured to: obtain biometric registration data associated with a user; generate a secret key for the biometric registration data, wherein the secret key indicates an index translate point array; determine enrollment data for the user based on an index translate function, the biometric registration data, and the secret key, wherein the index translate function modifies entries of the biometric registration data based on the index translate point array; generate one or more cryptographic keys for the user based on the index translate point array; and provide, to a computing platform, ancillary information associated with the one or more cryptographic keys and the enrollment data.

Abstract: In some instances, a method for verifying communication paths is provided. The method comprises: obtaining, from a first user device, a request to access content associated with a relying party system, wherein the request indicates user credentials and a first session identifier (ID); obtaining one or more quick response (QR) codes and a second session ID associated with a first QR code of the one or more QR codes, wherein the relying party system generates and provides the first QR code to the first user device; and verifying the first session ID and the second session ID, wherein the relying party system grants the first user device access to the requested content based on the verification.

Abstract: A method for authenticating a user is provided. The method comprises: providing first biometric enrollment data of the user to a first enrollment system of a plurality of enrollment systems; receiving a first enrollment identifier identifying the first enrollment system; storing the first enrollment identifier identifying the first enrollment system into a digital wallet of the user; in response to a request to access content on a relying party system, providing a biometric marker of the user and the first enrollment identifier from the digital wallet of the user to the relying party system; based on the relying party system identifying the first enrollment system using the first enrollment identifier and verifying the biometric marker of the user with the first enrollment system, accessing the requested content associated with the relying party system.

Abstract: A system and method are disclosed for detecting chronic health conditions based on data collected by a wearable device such as an activity tracker or a smart watch. Deep learning algorithms are configured to process the monitored parameter data collected by the wearable device as well as additional embedding data obtained from health records corresponding to a user account registered to the wearable device. In some examples, the input vector can also include embedding data related to social determinants data and/or demographic data. The output of the deep learning algorithms provides predictions that represent probabilities that the user of the wearable device has an underlying health condition. If any underlying health condition is detected, then the user can be notified directly, via the wearable device or an associated application or technology, or indirectly, via a primary care provider associated with the user.

Abstract: Embodiments of the disclosure provide a method for enhancing standard authentication systems to include risk-based decisions. Risk-based decisions can be selectively implemented within existing authentication systems to strategically modify and supplement security if an unacceptable risk is detected. Embodiments capture information pertaining to a user and user device. Information is stored to create a profile for the user and user device. A comparison between the stored information and live data can be performed within authentication systems to optimize security. If the results of the comparison demonstrate the presence of an acceptable risk, then the need for subsequent authentication can be reduced or eliminated, which improves a user experience.

Abstract: In some instances, a method for verifying communication paths is provided. The method comprises: obtaining, from a first user device, a request to access content associated with a relying party system, wherein the request indicates user credentials and a first session identifier (ID); obtaining one or more quick response (QR) codes and a second session ID associated with a first QR code of the one or more QR codes, wherein the relying party system generates and provides the first QR code to the first user device; and verifying the first session ID and the second session ID, wherein the relying party system grants the first user device access to the requested content based on the verification.

Abstract: In some instances, a user device for determining whether an individual is sick is provided. The user device is configured to obtain a facial image of an individual; obtain an audio file comprising a voice recording of the individual; determine a facial recognition confidence value associated with whether the individual is sick based on inputting the facial image into a facial recognition machine learning dataset that is individualized for the individual; determine a voice recognition confidence value associated with whether the individual is sick based on inputting the audio file into a voice recognition machine learning dataset that is individualized for the individual; determine whether the individual is sick based on the facial recognition confidence value and the voice recognition confidence value; and causing display of a prompt indicating whether the individual is sick.

Abstract: A unified data fabric for controlling data lifecycles and data flows between trusted data sources and data clients is described herein. A system can include a data ingestion engine and a data delivery engine. The data ingestion engine and the data delivery engine are connected to a data lifecycle engine that maintains data control policies and access control policies. The data ingestion engine is configured to control ingestion of data elements into the unified data fabric based on the data control policies, and the data delivery engine is configured to control access to data elements in the unified data fabric based on access control policies. Each data element from one or more trusted data sources is associated with a global identifier to provide a comprehensive view of information about a constituent from a variety of disparate data sources.

Abstract: In some instances, the disclosure provides a method for identifying access anomalies using network graphs. The method comprises obtaining access data for an entity, generating a network graph baseline profile based on the plurality of data elements, generating a network graph current profile based on the plurality of data elements, generating comparison data based on comparing the plurality of baseline network graphs with the one or more current network graphs and comparing the plurality of baseline nodes and the plurality of baseline edges with the plurality of current nodes and the plurality of current edges, determining, based on the comparison data, anomaly data comprising one or more flagged network accesses to the enterprise system, and providing the anomaly data indicating the flagged network accesses to an authentication system.

Abstract: Methods and systems for analyzing care data are described. The method includes building a virtual model of a physical medical device. Training is provided to a patient associated with the physical medical device to properly use the physical medical device by manipulating the virtual model. First care data associated with a first sensor associated with the physical medical device and second care data associated with a second sensor is received by a cloud service. The cloud service analyzes the first care data to obtain a first care data score and analyzes the second care data to obtain a second care data score. The cloud service scores, using a machine learning algorithm, the first care data score and the second care data score to obtain a combined care score. The cloud service determines whether the combined care score is greater than a threshold. The cloud service triggers an emergency procedure when it is determined that the combined care score is greater than the threshold.

Abstract: In some instances, a method for authenticating a user using key pair authentication is provided. The method comprises enrolling the user into key pair authentication by generating a private and public key pair for an authentication domain, accessing the content on the first domain based on enrolling the user into the key pair authentication with a key pair authentication server using the private and public key pair for the authentication domain, requesting access for different content on a second domain, based on enrolling the user into the key pair authentication for the first domain, redirecting a browser from the second domain to the authentication domain, and accessing the different content on the second domain based on performing the key pair authentication with the key pair authentication server using the private and public key pair for the authentication domain.

Abstract: Embodiments of the disclosure provide a system and method of allocating a resource based on myriad input data. In some embodiments, the myriad input data include membership information, claims data, transactional data, etc. The myriad input data are sorted and organized in a meaningful association relationship before applied to a resource allocation modeling algorithm. The resource allocation modeling algorithm provides estimated resource necessary for the application chosen. For example, an insurance company may use membership information, claims data, transactional data, etc., to estimate how much reserves or funds it should hold to cover future claims within a certain timeframe.

Abstract: In some instances, the disclosure provides a method performed by a smart vital device. The method comprises receiving sensor information indicating one or more health characteristics associated with an individual, wherein the sensor information comprises audio information indicating audio signals from a surrounding environment and temperature information indicating temperature readings from the surrounding environment, determining one or more health audio characteristics of the individual based on inputting the audio signals into one or more health condition machine learning datasets, determining one or more health temperature characteristics of the individual based on the temperature readings from the surrounding environment, determining one or more health conditions of the individual based on the one or more health audio characteristics and the one or more health temperature characteristics, and outputting the one or more health conditions of the individual.

Abstract: Embodiments of the disclosure provide a method for enhancing standard authentication systems to include risk-based decisions. Risk-based decisions can be selectively implemented within existing authentication systems to strategically modify and supplement security if an unacceptable risk is detected. Embodiments capture information pertaining to a user and user device. Information is stored to create a profile for the user and user device. A comparison between the stored information and live data can be performed within authentication systems to optimize security. If the results of the comparison demonstrate the presence of an acceptable risk, then the need for subsequent authentication can be reduced or eliminated, which improves a user experience.

Abstract: In some instances, the disclosure provides a method for managing and updating contextual intelligent processes using artificial intelligence algorithms. The method comprises obtaining, from a user device, health information indicating a health triggering event associated with a user, obtaining event information associated with the user, determining, based on the health triggering event, one or more contextual intelligent processes for the health triggering event, retrieving one or more contextual artificial intelligence datasets, updating the one or more contextual intelligent processes with at least one new service based on inputting the health triggering event, the event information, and the one or more contextual intelligent processes into the one or more contextual artificial intelligence datasets, and performing the one or more updated contextual intelligent processes.

Abstract: Embodiments of the disclosure provide a method for aggregating and providing health data records to an electronic device. The method is performed by a server that includes a processor and a non-transitory computer readable medium with processor-executable instructions stored thereon. When the instructions are executed by the processor, the server performs the method including: (a) receiving collected data from one or more client devices, the collected data comprising health related data including at least one of step count data, heart rate data, sleep sensor data; (b) extracting metadata from the collected data; (c) pseudonymizing the collected data; (d) categorizing the collected data using the extracted metadata and enterprise ontology of the server; and (e) storing the collected data.

Abstract: Global identity contexts are established for unique constituents to interact with a cloud architecture through a variety of relationships. The global identity context enables a particular constituent to access services from different cloud-service providers in a secure and simplified manner. Authenticating one account can provide access to services associated with other accounts linked to the global identity context for the authenticated account. In some embodiments, the global identity platform includes an account management application and an identity management application. The account management application is configured to register one or more accounts for each constituent. The identity management application is configured to perform individualization to establish an individual identifier for each unique constituent and map each account to a particular individual identifier and one or more local identifiers.

Abstract: A method of integrating data across multiple data stores is provided. The method includes ingesting diverse data from multiple data sources and reconciling the ingested diverse data by updating semantic models based on the ingested diverse data. The method further includes storing the ingested diverse data based on one or more classification of the data sources according to the semantic models and automatically generating scalable service endpoints that are semantically consistent according to the classification of the data sources. The generated scalable service endpoints are application programming interfaces. The method also includes determining a protocol based on the scalable service endpoints in response to receiving a call from the one or more recipient systems and responding to the call from the one or more recipient systems by providing data in the classification of the data sources.