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.

Abstract: A system and method are disclosed for creating solution design blueprints. A solution design blueprint is a machine-readable data structure that includes a conceptual design model for an application framework. A user interface is configured to receive a plain language textual request from a user that describes a desired application or solution to a problem. Artificial Intelligence is leveraged to fit the textual request to semantic data models and map elements of the textual request to components of a design library. The resulting solution design blueprint can be presented to a user, and the user interface can be used to provide feedback related to the solution design blueprint that can be utilized to update machine learning algorithms and/or neural networks. In some embodiments, the solution design blueprint can be converted to an application framework that is provided to the use in an integrated development environment of the user interface.

Abstract: A system and method are disclosed for detecting anomalies in input data. The input data can include enrollment information for members of a health insurance product offered by an insurance carrier. A system is configured to process one or more parameters associated with the input data to detect whether an anomaly is indicated in the input data. At least one artificial intelligence algorithm is configured to compare a parameter in the one or more parameters to a range defined by a moving average. When an anomaly is detected, the processing can be paused and manual intervention can be facilitated. When no anomaly is detected, a database is updated based on the input data. In an embodiment, the input data is an ANSI 834 format file that includes a plurality of membership records, and the one or more parameters are derived from statistics related to the membership records.

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: Systems and methods for providing independent situational awareness messages are provided. The method includes receiving, by a rendering engine, a request for information from an input interface. The rendering engine queries at least one data store in response to the request. The rendering engine obtains public content data and private content data from the data store. The rendering engine transmits the public content data over a public output interface. The rendering engine transmits the private content data over a private output interface.

Abstract: In some instances, a fall detection system comprising a first fall detection device and a user device is provided. The fall detection device is configured to: detect an occurrence of a fall event associated with an individual based on sensor information from the one or more sensors and a fall detection model; and provide a first indication indicating the occurrence of the fall event. The user device is configured to: receive the first indication; cause display of a prompt requesting user feedback as to whether the individual fell based on the first indication and a second indication from a second fall detection device; provide update information indicating for the first fall detection device to update the fall detection model based on the user feedback; and provide user fall information associated with the occurrence of the fall event based on the user feedback.

Abstract: Methods and systems for performing a search over hierarchical data are provided. The method may be performed by a server comprising a processor and memory. The method includes receiving a query string from a user device. The query string is searched for via a tensor search of a graph structure to determine node tensor distance score for each node in the graph structure. The query string is searched for via a fuzzy search of the graph structure to determine node fuzzy distance score for each node in the graph structure. Nodes with relevant scores are determined by updating a Bayesian network representation with evidence based on the node tensor distance scores and the node fuzzy distance scores of each node. Relevant data from the nodes is sent with relevant scores to the user device.

Abstract: A method for performing searches of user information comprises: receiving an initial dataset including the user information; calculating distance metrics between pairs of data in the initial dataset; performing unsupervised learning on the initial dataset to obtain a plurality of total number of clusters, each total number of clusters covering the initial dataset; determining efficacy measures for each total number of clusters using a plurality of distance metric thresholds; determining a desired efficacy measure in the efficacy measures, the desired efficacy measure corresponding to a desired distance metric threshold in the plurality of distance metric thresholds; determining a desired total number of clusters in the plurality of total number of clusters, the desired total number of clusters corresponding to the desired distance metric threshold; and performing unsupervised learning on the initial dataset using the desired total number of clusters to obtain a number of data representations of the user infor

Abstract: A system includes at least one web server, a storage, and a suspicious access attempt detector. The at least one web server is configured to receive and process a plurality of access attempts from a plurality of user devices over a network, and to provide access attempt information corresponding to the plurality of access attempts to a storage, wherein access attempt information for each respective access attempt comprises an access signature corresponding to the respective access attempt. The suspicious access attempt detector configured to: obtain the access attempt information corresponding to the plurality of access attempts from the storage; analyze the access attempt information corresponding to the plurality of access attempts to detect suspicious access attempts out of the plurality of access attempts, wherein analyzing the access attempt information is based on respective access signatures corresponding to the plurality of access attempts; and output a result of the detection.