Abstract: Various embodiments of the present disclosure provide methods, apparatuses, systems, computing devices, computing entities, and/or the like for detecting and preventing seizure events in real-time. For example, various embodiments provide techniques for detecting and preventing seizure events in real-time that use seizure prediction machine learning models.

Abstract: Various embodiments of the present invention provide methods, apparatus, systems, computing devices, computing entities, and/or the like for performing predictive respiratory quality score assignment. Certain embodiments of the present invention utilize systems, methods, and computer program products that perform predictive respiratory quality score assignment using at least one of respiratory quality evaluation scoring machine learning models, explanation generation machine learning model, supplemental feature extraction machine learning model, and observed sensory data.

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: There is a need to automatically provide one or more electronic documents to the user. In one example, embodiments comprise, generating a facility visit data object for a user describing one or more facility attributes for one or more facilities associated with a potential visit from the user. One or more electronic documents may be determined to be retrieved based at least in part on the facility visit data object. One or more user interaction electronic document data objects may be generated to enable interaction between the user and the one or more electronic document data objects. One or more modified user interaction electronic document data objects may be received and may be provided to one or more facility computing entities in response to one or more trigger events.

Abstract: Embodiments of the invention provide apparatuses, systems, and methods for more accurate remote monitoring of a user’s body. In some embodiments, a system for monitoring a user’s body comprises a wearable device, a video sensor attached at a collar portion of the wearable device, a plurality of audio sensors spaced and attached at a body portion of a wearable device and a controller configured to determine a Jugular Venous Pressure (JVP) of the user, and determine audio characteristics of an output of the plurality of audio sensors to generate an audio heat map corresponding to at least one internal organ of the user.

Abstract: An automated system and corresponding method is configured to predict a call duration of a customer service interaction between a caller and a customer-service agent of a call center, based at least in part on information provided orally by the caller to the automated system. The automated system transcribes the orally provided information, preprocesses the transcribed data, adds feature enrichment data to supplement the transcribed data, and executes a machine-learning model to predict the caller’s intent. If the predicted caller’s intent does not have an adequate confidence score associated therewith, the system requests additional data from the caller, and supplements the original data with newly provided data, and again determines a predicted call intent. This process may iterate until the confidence score satisfies applicable confidence criteria prior to utilizing two additional machine-learning models to predict a call duration of the interaction between the caller and a customer-service agent.

Abstract: A method, computer program product, and a system where a processor(s) obtains data related to physical activities performed by an individual from a sensor(s) proximate to the individual. The processor(s) cognitively analyzes the data to identify baseline behavioral patterns of the individual, when the individual is engaged in each of the physical activities. The processor(s) obtains data indicating consumption of a substance by the individual at a first time. The processor(s) determines impacts of the consumption on the baseline behavioral patterns of the individual and generates a data structure (a predictive model) that includes expected deviations from the baseline behavioral patterns of the individual, when the individual has consumed the substance.

Abstract: To schedule a future interaction between a caller and a call-center, a management computing system associated with the call center is configured to determine an estimated call time for addressing the caller's issues, based at least in part on a predicted call intent as well as feature enrichment data received from one or more memory storage areas. Upon determining a predicted call duration for the call, the management computing entity accesses the caller's calendar, such as through an internet-based communication between the caller's user computing entity and the management computing entity, or via third-party access permissions provided by the caller. The management computing entity identifies one or more candidate timeslots based at least in part on the predicted call duration, and receives user input selecting a candidate timeslot for scheduling the callback.

Abstract: A computer-implemented method for controlling a vehicle. The method monitors one or more characteristics of one or more users within the vehicle, and compares the one or more characteristics of the one or more users with one or more corresponding baseline characteristics of the one or more users. The method further determines, based on the comparison, that a difference between the one or more characteristics and the one or more corresponding baseline characteristics of the one or more users exceeds a threshold value, and performs a controlling action associated with the vehicle, wherein the controlling action may be taking a higher level of autonomous control over the vehicle; varying speed and handling of the vehicle; and overriding the one or more characteristics of the one or more users in order to avoid an accident.

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: Techniques are described with respect to addressing at least one sensor abnormality associated with a vehicle. An associated method includes receiving a first measurement value from a first sensor among a plurality of sensors associated with a vehicle and receiving a second measurement value from a second sensor among the plurality of sensors. The method further includes identifying at least one sensor abnormality based upon an inconsistency between the first measurement value and the second measurement value. In an embodiment, the at least one sensor abnormality results from at least one sensor defect, at least one vehicle security fault, or a combination thereof. The method further includes completing at least one predefined action to address the at least one sensor abnormality.

Abstract: In an approach to facilitating data transmission utilizing peer-to-peer communications and wireless ad hoc networks, one or more computer processors detect one or more data transmission failures. The one or more computer processors rank the one or more detected data transmission failures. The one or more computer processors detect one or more subsequent devices. The one or more computer processors determine one or more statuses associated with the detected one or more subsequent devices. The one or more computer processors the one or more detected subsequent devices based on the determined the determined statuses. The one or more computer processors match the one or more ranked data transmission failures with the one or more ranked subsequent devices. The one or more computer processors transmit the one or more data transmission failures with one or more matched subsequent devices.

Abstract: A controller for an artificial heart enables activity-specific adjustments to the operation of an artificial heart by obtaining sensor data from a plurality of sensors monitoring characteristics of a patient's body, and using the sensor data as input to one or more control parameter models for identifying control parameters to be provided to the artificial heart to adjust the operational parameters of the artificial heart. The controller is in wireless communication with the artificial heart via an application program interface (API)-based communication channel that facilitates communication between the controller and the artificial heart. Moreover, a cloud-based management computing entity may be utilized to train and/or execute one or more models to enable real-time updates to the operational characteristics of the artificial heart to enable the artificial heart to appropriately accommodate activities of the patient.

Abstract: A controller for an artificial heart enables activity-specific adjustments to the operation of an artificial heart by obtaining sensor data from a plurality of sensors monitoring characteristics of a patient's body, and using the sensor data as input to one or more control parameter models for identifying control parameters to be provided to the artificial heart to adjust the operational parameters of the artificial heart. The controller is in wireless communication with the artificial heart via an application program interface (API)-based communication channel that facilitates communication between the controller and the artificial heart. Moreover, a cloud-based management computing entity may be utilized to train and/or execute one or more models to enable real-time updates to the operational characteristics of the artificial heart to enable the artificial heart to appropriately accommodate activities of the patient.

Abstract: Various embodiments of the present invention provide methods, apparatus, systems, computing devices, computing entities, and/or the like for performing optimized equipment allocation. Certain embodiments of the present invention utilize systems, methods, and computer program products that perform optimized equipment allocation using at least one of equipment evaluation scoring machine learning models, equipment optimized allocation machine learning models, and equipment history events.

Abstract: Data ownership of a single record data object comprising a plurality of individual data elements may be distributed across a plurality of users, such that each individual user is capable of separately controlling access to those data elements for which the data owner has ownership privileges. These data ownership privileges, and corresponding access rights which may be individually provided by distinct data owners, is managed by a data management computing entity such that a single composite user interface may be generated for a user viewing a particular record data object such that the viewer is provided with viewing access to only those data elements for which the viewer has access. Thus, separate user interfaces may be generated and provided for different viewers accessing the same record data object.

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.

Abstract: Methods and systems for presenting a proactive audiovisual query using a virtual assistant software application. The methods correspond to retrieving user experience data associated with a user profile for the virtual assistant software application, wherein the user experience data define one or more user experience events for the user profile. The methods further include retrieving subject matter domain data associated with the one or more user experience events, wherein the subject matter domain data define one or more probabilistic event effects for the one or more user experience events and determining, based on the user experience data and the subject matter domain data, one or more optimal query items, wherein the one or more optimal query items are associated with at least one of the one or more probabilistic event effects. The methods further include generating the proactive audiovisual query in accordance with the one or more optimal query items.