Abstract: Methods, systems, and non-transitory computer readable mediums are disclosed for recommending medically-relevant articles. One method comprises receiving health data associated with a patient, storing the health data in a data structure as historical patient data, identifying new appointment scheduling data associated with the patient, determining an appointment subject associated with the new appointment scheduling data, determining a correlation between the new appointment scheduling data and the historical patient data, searching one or more databases for one or more relevant articles, retrieving the one or more relevant articles, generating a recommendation for the one or more relevant articles, and presenting the recommendation for the one or more relevant articles to a user through at least one of a news feed, a calendar, or an electronic medical record (EMR) associated with the patient.

Abstract: An example method includes obtaining, by processing circuitry, an image depicting a face of a person wearing eyewear and a reflection pattern generated by projecting light onto a lens of the eyewear and determining, by the processing circuitry, an optical parameter of the lens based on the image. The method further includes receiving, by the processing circuitry and from an electronic database, a personal characteristic data relating to a previously identified person and comparing, by the processing circuitry, the optical parameter of the lens to the personal characteristic data. The method further includes determining, by the processing circuitry and based on the comparison, a score indicative of a match between the person wearing eyewear and the previously identified person.

Abstract: Various embodiments of the present disclosure provide methods, apparatus, systems, computing devices, computing entities, and/or the like for multi-node system monitoring using one or more distributed ledgers, wherein a ledger entry request received from a miner node computing entity is validated based at least in part on executing a hierarchical validation workflow that comprises an ordered sequence of L validation iterations, wherein each of one or more ith non-initial validation iterations is performed based at least in part on an association of an (i?1)th validation iteration with a non-affirmative validation determination.

Abstract: Various embodiments of the present invention disclose techniques for traversal path optimization given a traversal network comprising a group of nodes comprising a plurality of navigation orchestration nodes and using a traversal path optimization machine learning model. In some embodiments, a path feature set is determined for each candidate traversal path of a plurality of candidate traversal paths. A traversal path optimization machine learning model is configured to generate path scores for each candidate traversal path based at least in part on the path feature set.

Abstract: As described herein, various embodiments of the present invention use an output space refinement machine learning model to filter C of the B candidate predictive associations that are referred to herein as dynamically-preselected candidate predictive associations for each prediction input data object, with every prediction input data object being associated with a different subset of the dynamically-preselected candidate predictive associations, where C is less than B and is in some embodiments typically much less than B. As described in greater detail below, this approach reduces the number of computational operations that need to be performed by a final classification machine learning model (referred to herein as a variable-output-space prediction machine learning model), and leads to substantial computational efficiency advantages relative to naïve implementations.

Abstract: Various embodiments of the present invention provide methods, apparatus, systems, computing devices, computing entities, and/or the like for performing predictive data analysis operations configured to integrate distinct clustering schemes given temporal variations. For example, certain embodiments of the present invention utilize systems, methods, and computer program products that perform predictive data analysis operations by generating integrative predicted scores based at least in part on at least one of: within-cluster consistency scores determined for clusters determined using a first clustering scheme (e.g., a service clustering scheme), within-cluster consistency scores determined for clusters determined using a second clustering scheme (e.g., a recipient clustering scheme), cross-cluster consistency scores, and cross-temporal consistency scores.

Abstract: An example method for generation of travel-booking user interfaces, the method including receiving, by a computing system, a user interface request to present to a user a travel-booking user interface that indicates one or more available voyages from an originating location to a destination location, determining, by the computing system and for each respective voyage of the one or more available voyages, a user-specific incentive for the respective voyage that is based at least in part on applicable healthcare skills of the user and health metrics of passengers that are already booked for the respective voyage, wherein the applicable healthcare skills include healthcare skills that are applicable to an in-voyage medical emergency, and generating, by the computing system and based on the user interface request, the travel-booking user interface based on the determined user-specific incentive.

Abstract: An example method comprises determining, by a computing system, that a message-sending computing device has received an indication of user input indicating an intent to send a message to a user of a message-recipient computing device; prior to the message being delivered to the message-recipient computing device, calculating, by the computing system, a screen sharing risk score (SSRS) that indicates a risk that the message-recipient computing device is currently sharing screen content of a screen of the message-recipient computing device with a screen-recipient computing device associated with an untrusted screen-recipient user; and based on the SSRS indicating that the risk is above a risk threshold, causing the message-sending computing device to output an alert indicating that the message-recipient computing device is possibly sharing the screen content of the message-recipient computing device with the screen-recipient computing device associated with the untrusted screen-recipient user.

Abstract: A method comprising: monitoring, by a computing system, a callee device for missed phone calls from a caller; determining, by the computing system, based on a behavioral history of the callee, callee health parameters of the callee, and a number of the missed phone calls from the caller, whether an unresponsiveness condition is satisfied; and based on a determination that the unresponsiveness condition is satisfied and in response to a missed phone call from the caller, causing a caller device to present callee health data to the caller.

Abstract: Methods, apparatuses, systems, computing devices, and/or the like are provided. An example method may include generating edges connecting attribute vertices to a member vertex in a healthcare graph data object, determining, using at least one graph-based machine learning model and based at least in part on the attribute vertices, historical member vertices from the healthcare graph data object, determining, using the at least one graph-based machine learning model and based at least in part on the historical member vertices, historical member query vertices from the healthcare graph data object, generating, based at least in part on the historical member query vertices, predicted member query vertices in the healthcare graph data object, and performing one or more prediction-based actions based at least in part on the one or more predicted member query vertices.

Abstract: An example method includes obtaining, by processing circuity, an image depicting a face of a person wearing eyewear and a reflection pattern generated by projecting light onto a lens of the eyewear and determining, by the processing circuitry, an optical parameter of the lens based on the image. The method further includes receiving, by the processing circuitry and from an electronic database, a personal characteristic data relating to a previously identified person and comparing, by the processing circuitry, the optical parameter of the lens to the personal characteristic data. The method further includes determining, by the processing circuitry and based on the comparison, a score indicative of a match between the person wearing eyewear and the previously identified person.

Abstract: There is a need for more accurate and more efficient optimized scheduling operations. This need can be addressed by, for example, techniques for performing one or more optimized scheduling operations. In one example, a method includes: determining, using an optimal event time prediction learning machine model, a predicted interactivity measure for an event data object; determining, based at least in part on the predicted interactivity measure and using an optimal event time prediction machine learning model, an optimal event time modification value for the event data object; and determining, by one or more processors, an optimized appointment prediction based at least in part on optimal event time modification value.

Abstract: A computing device may receive, from a remote computing device, a request to establish a communication session with the remote computing device and contextual information indicative of an urgency level of the communication session. The computing device may output, at one or more output devices, the contextual information indicative of the urgency level of the communication session and at least one of: haptic output or an audible alert that indicates the request to establish the communication session.

Abstract: To provide objective indications of the progression of peripheral neuropathy of patients, a transmitter apparatus is utilized to produce reproducible pulse signals to specified locations on the human body to determine a minimum level of stimulation necessary to elicit a consciously detectable sensation through the generation of a series of pulse signals of varying intensities, and the recordation of the number of pulse signals felt by the patient. Moreover, the nerve velocity of the patient is additionally determined for a patient via the transmitter apparatus and a receiver apparatus detecting body-signals passing along a nerve within the patient and corresponding to the pulse signals applied to the patient. The results of these tests are recorded over time, thereby enabling generation of patient-specific models indicative of the progression of the patient's peripheral neuropathy over time.

Abstract: An example method comprises determining, by a computing system, that a message-sending computing device has received an indication of user input indicating an intent to send a message to a user of a message-recipient computing device; prior to the message being delivered to the message-recipient computing device, calculating, by the computing system, a screen sharing risk score (SSRS) that indicates a risk that the message-recipient computing device is currently sharing screen content of a screen of the message-recipient computing device with a screen-recipient computing device associated with an untrusted screen-recipient user; and based on the SSRS indicating that the risk is above a risk threshold, causing the message-sending computing device to output an alert indicating that the message-recipient computing device is possibly sharing the screen content of the message-recipient computing device with the screen-recipient computing device associated with the untrusted screen-recipient user.

Abstract: A method comprises obtaining a video stream of a first party who is engaging with a second party in a telemedicine session; determining statuses of one or more privacy aspects of a first party environment, wherein the privacy aspects of the first party environment are aspects of the first party environment that have a potential to compromise privacy of sensitive information provided by the second party to the first party during the telemedicine session; and causing a second party computing device to present a user interface of a telemedicine facilitation application, wherein the user interface of the telemedicine facilitation application includes the video stream of the first party and also includes a set of one or more notifications, wherein each of the one or more notifications indicates the status of a different one of the privacy aspects of the first party environment.