Abstract: Techniques are provided for computing with private healthcare data. The techniques include a de-identification method including receiving a text sequence; providing the text sequence to a plurality of entity tagging models, each of the plurality of entity tagging models being trained to tag one or more portions of the text sequence having a corresponding entity type; tagging one or more entities in the text sequence using the plurality of entity tagging models; and obfuscating each entity among the one or more tagged entities by replacing the entity with a surrogate, the surrogate being selected based on one or more attributes of the entity and maintaining characteristics similar to the entity being replaced.

Abstract: Techniques are provided for computing with private healthcare data. The techniques include a de-identification method including receiving a text sequence; providing the text sequence to a plurality of entity tagging models, each of the plurality of entity tagging models being trained to tag one or more portions of the text sequence having a corresponding entity type; tagging one or more entities in the text sequence using the plurality of entity tagging models; and obfuscating each entity among the one or more tagged entities by replacing the entity with a surrogate, the surrogate being selected based on one or more attributes of the entity and maintaining characteristics similar to the entity being replaced.

Abstract: Techniques are provided for computing with private healthcare data. The techniques include a method comprising constructing an isolated memory partition that forms a secure enclave and pre-provisioning software within the secure enclave. The pre-provisioned software is configured to receive at least one of input data or the instructions for the one or more application computing processes in an encrypted form; decrypt the at least one of input data or instructions using one or more cryptographic keys; execute the one or more application computing processes based on the decrypted at least one of input data or instructions to generate output data; generate a proof of execution that indicates that the one or more application computing processes operated on the received input data; encrypt the output data using the one or more cryptographic keys; and provide external access to the encrypted output data and the proof of execution.

Abstract: An apparatus for generating a dictionary data filter for data deidentification is disclosed. The apparatus includes at least processor and a memory communicatively connected to the processor. The memory instructs the processor to receive a plurality of user data. The memory instructs the processor to generate contextual data as a function of the plurality of user data. The memory instructs the processor to identify a plurality of patient identifiers and a plurality of localized terms within the plurality of user data. The memory instructs the processor to generate a dictionary data filter as a function of the plurality of localized terms. The memory instructs the processor to identify one or more misidentified patient identifiers within the plurality of patient identifiers using the dictionary data filter. The memory instructs the processor to modify the plurality of patient identifiers as a function of the one or more misidentified patient identifiers.

Abstract: Systems and methods are described herein for updating links between keywords associated with a trending topic. Control circuitry may identify a plurality of communications associated with a plurality of users, the plurality of communications being related to a topic. The communications may comprise, for example, emails, text messages, online social media posts, websites or portions of a website, or any other online communication. The control circuitry may determine whether the topic is trending and increase a strength of association between a first symbol associated with the topic and a second symbol associated with the topic such that when a search query is received that includes the first symbol, search results related to the second symbol have a higher probability of being returned.

Abstract: Methods and systems are described herein to recommend media assets to a user based on user location. A media guidance application may identify, using control circuitry, a user location. The media guidance application may generate a list of a plurality of media assets that match a user profile. The media guidance application may determine whether subject matter of a first media asset of the plurality of media assets is inconsistent with the user location. The media guidance application may remove the first media asset from the list in response to determining that the subject matter of the first media asset is inconsistent with the user location.

Abstract: An apparatus for the anonymization of user data is disclosed. The apparatus includes at least processor and a memory communicatively connected to the processor. The memory contains instructions configuring the processor to receive a plurality of user data. The memory contains instructions configuring the processor to identify a plurality of patient identifiers within the plurality of user data. The memory contains instructions configuring the processor to generate contextual data associated with each patient identifier of the plurality of patient identifier. The memory contains instructions configuring the processor to identify one or more false positive patient identifiers within the plurality of patient identifiers as a function of the contextual data.

Abstract: Systems and methods are described herein for controlling mobile devices with user equipment devices. A user equipment device may detect a mobile device is within a predetermined proximity to the user equipment device by establishing a bi-directional communication. The user equipment device may determine an input/output option of the mobile device. The input/output option may be a microphone, a cellular Internet connection, a camera, or any other sensor and/or actuator of the mobile device. The user equipment device may generate for display an icon corresponding to the input/output option of the mobile device.

Abstract: Methods and systems are described for a media guidance application that tailors media content recommendations for downloadable content to the current interests of the users. For example, the media guidance application may determine the current interests of a user based on the media content recently consumed by the friends of the user, and automatically download that media content. In such cases, the media guidance application may monitor social networks of the user for indications of media content that may have been recently consumed by the friends of a user as such media content is likely to be of current interest to the user. In response to detecting media content that was recently consumed by the friend of the user, the media guidance application may automatically download the media content to a device of the user.

Abstract: Methods and systems are described for a media guidance application that tailors media content recommendations for downloadable content to the current interests of the users. For example, the media guidance application may determine the current interests of a user based on the media content recently consumed by the friends of the user, and automatically download that media content. In such cases, the media guidance application may monitor social networks of the user for indications of media content that may have been recently consumed by the friends of a user as such media content is likely to be of current interest to the user. In response to detecting media content that was recently consumed by the friend of the user, the media guidance application may automatically download the media content to a device of the user.

Abstract: Systems and methods are described herein for controlling mobile devices with user equipment devices. A user equipment device may detect a mobile device is within a predetermined proximity to the user equipment device by establishing a bi-directional communication. The user equipment device may determine an input/output option of the mobile device. The input/output option may be a microphone, a cellular Internet connection, a camera, or any other sensor and/or actuator of the mobile device. The user equipment device may generate for display an icon corresponding to the input/output option of the mobile device.

Abstract: An apparatus for anonymizing user data is disclosed. The apparatus includes at least a processor and a memory communicatively connected to the at least a processor. The memory instructs the processor to receive, from a first database, a plurality of user data comprising a plurality of metadata. The memory instructs the processor to detach the plurality of metadata for the plurality of user data. The memory instructs the processor to identify a plurality of patient identifiers within the plurality of user data and the plurality of metadata. The memory instructs the processor to generate a plurality of anonymized data and anonymized metadata as a function of the plurality of patient identifiers and the plurality of metadata using an anonymization machine learning model. The memory instructs the processor to construct a plurality of anonymized user records as a function of the plurality of anonymized data.

Abstract: Techniques are provided for computing with private healthcare data. The techniques include a de-identification method including receiving a text sequence; providing the text sequence to a plurality of entity tagging models, each of the plurality of entity tagging models being trained to tag one or more portions of the text sequence having a corresponding entity type; tagging one or more entities in the text sequence using the plurality of entity tagging models; and obfuscating each entity among the one or more tagged entities by replacing the entity with a surrogate, the surrogate being selected based on one or more attributes of the entity and maintaining characteristics similar to the entity being replaced.

Abstract: Techniques are provided for computing with private healthcare data. The techniques include a method comprising constructing an isolated memory partition that forms a secure enclave and pre-provisioning software within the secure enclave. The pre-provisioned software is configured to receive at least one of input data or the instructions for the one or more application computing processes in an encrypted form; decrypt the at least one of input data or instructions using one or more cryptographic keys; execute the one or more application computing processes based on the decrypted at least one of input data or instructions to generate output data; generate a proof of execution that indicates that the one or more application computing processes operated on the received input data; encrypt the output data using the one or more cryptographic keys; and provide external access to the encrypted output data and the proof of execution.

Abstract: Techniques are provided for computing with private healthcare data. The techniques include a method comprising constructing an isolated memory partition that forms a secure enclave and pre-provisioning software within the secure enclave. The pre-provisioned software is configured to receive at least one of input data or the instructions for the one or more application computing processes in an encrypted form; decrypt the at least one of input data or instructions using one or more cryptographic keys; execute the one or more application computing processes based on the decrypted at least one of input data or instructions to generate output data; generate a proof of execution that indicates that the one or more application computing processes operated on the received input data; encrypt the output data using the one or more cryptographic keys; and provide external access to the encrypted output data and the proof of execution.

Abstract: Techniques are provided for computing with private healthcare data. The techniques include a de-identification method including receiving a text sequence; providing the text sequence to a plurality of entity tagging models, each of the plurality of entity tagging models being trained to tag one or more portions of the text sequence having a corresponding entity type; tagging one or more entities in the text sequence using the plurality of entity tagging models; and obfuscating each entity among the one or more tagged entities by replacing the entity with a surrogate, the surrogate being selected based on one or more attributes of the entity and maintaining characteristics similar to the entity being replaced.

Abstract: Methods and systems are provided for generating a response to a natural language query. Specifically, the natural language query is received and a query template that corresponds to the natural language query is determined. One or more search results corresponding to the natural language query are retrieved. One or more attributes associated with a user are selected based on selection criteria. Based on those attributes, a response template previously assigned to the query template is identified. A response to the natural language query is generated based on the identified response template and the retrieved one or more search results.

Abstract: Methods and systems are disclosed herein for accurately training a machine learning model with a reduced training data set. A large number of data records may be parsed. Each record may be reduced to a set of symbols representing the composition of each record. A user may assign a classification to each symbol within each record. Records with identical arrangements and classifications of symbols may be grouped together, and a representative sample of data records from each group may be fed into the model as the reduced training data set.

Abstract: The present disclosure provides systems and methods for selecting and presenting content items based on user input. The method includes receiving first input intended to identify a desired content item among content items associated with metadata, determining that an input portion has an importance measure exceeding a threshold, and providing feedback identifying the input portion. The method further includes receiving second input, and inferring user intent to alter or supplement the first input with the second input. The method further includes, upon inferring intent to alter the first input, determining an alternative query by modifying the first input based on the second input, and, upon inferring intent to supplement the first input, determining an alternative query by combining the first input and the second input. The method further includes selecting and presenting a subset of content items based on comparing the alternative query and metadata associated with the subset.

Abstract: Techniques are provided for computing with private healthcare data.