Abstract: To train models, training data is needed. As personal data changes over time, the training data can get stale, obviating its usefulness in training the model. Embodiments deal with this by developing a database with a running log specifying how each person's data changes at the time. When data is ingested, it may not he normalized. To deal with this, embodiments clean the data to ensure the ingested data fields are normalized. Finally, the various tasks needed to train the model and solve for accuracy of personal data can quickly become cumbersome to a computing device. They can conflict with one another and compete inefficiently for computing resources, such as processor power and memory capacity. To deal with these issues, a scheduler is employed to queue the various tasks involved.

Abstract: The present disclosure relates to compositions, methods and kits for the isolation of extracellular vesicles. The compositions, methods and kits can comprise a high-density liquid reagent that facilitates the sequestration of extracellular vesicles bound to magnetic beads.

Abstract: Disclosed herein are system, method, and computer program product embodiments for linking data records in memory. The system, method, and computer program product includes accessing a first record stored in memory, the first record holding information describing a first person and accessing at least one additional record stored in memory, the additional records holding information describing additional persons. The method continues by parsing the information of the first record and additional record and assigning the parsed information to predefined categories within the respective records. After assigning the information into categories, a similarity score between categorical information in the first record and categorical information of additional records is determined. A category of an additional record is then modified based on the similarity score, so the additional record is associated with the first person.

Abstract: Methods, systems, and products authenticate users for access to devices, applications, and services. Skills of a user are learned over time, such that an electronic model of random subject matter may be generated. The user is prompted to interpret the random subject matter, such as with an electronic drawing. The user's interpretation is then compared to the electronic model of the random subject matter. If the user's interpretation matches the electronic model, the user may be authenticated.

Abstract: A system is provided for driving an implantable neurostimulator lead, the lead having an associated plurality of electrodes disposed in at least one array on the lead. The system comprises an implantable pulse generator (IPG), the IPG including an electrode driver, a load system for determining load requirements, an IPG power coupler, and an IPG communication system. The system also includes an external unit, which includes an external variable power generator, an external power coupler, an external communication system, and a controller for varying the power level of the variable power generator.

Abstract: A method for subcutaneously treating pain in a patient includes first providing a neurostimulator with an IPG body and at least a primary integral lead with electrodes disposed thereon. A primary incision is opened to expose the subcutaneous region below the dermis in a selected portion of the body. A pocket is then opened for the IPG through the primary incision and the primary integral lead is inserted through the primary incision and routed subcutaneously to a first desired nerve region along a first desired path. The IPG is disposed in the pocket through the primary incision. The primary incision is then closed and the IPG and the electrodes activated to provide localized stimulation to the desired nerve region and at least one of the nerves associated therewith to achieve a desired pain reduction response from the patient.

Abstract: In some examples, an electronic device records, in an entry of a time-state data structure that includes a plurality of entries to store respective times, a time in response to invocation of a time-lapse process that lasts a predefined time duration independently of a time clock of the electronic device. The electronic device determines whether times in successive entries of the plurality of entries of the time-state data structure are within a threshold of one another, the threshold based on the predefined time duration. Based on the determining, the electronic device sets a parameter representing a quality of the time clock.

Abstract: A system is provided for driving an implantable neurostimulator lead, the lead having an associated plurality of electrodes disposed in at least one array on the lead. The system comprises an implantable pulse generator (IPG), the IPG including an electrode driver, a load system for determining load requirements, an IPG power coupler, and an IPG communication system. The system also includes an external unit, which includes an external variable power generator, an external power coupler, an external communication system, and a controller for varying the power level of the variable power generator.

Abstract: Disclosed herein are system, method, and computer program product embodiments for determining a first processing demand required to clean a data set and identifying one or more processors to clean the data based on the determined demand. The system, method, and computer program product embodiment further monitors the data cleaning process to determine a second demand and decides whether to continue operating one or more of the processors, based on the second demand.

Abstract: A cell monitoring plate comprises a flat surface on which multiple cell culturing vessels may be stacked. The flats surface has multiple optical imaging systems embedded therein to fully image a cell culture vessels stacked on the plate. Each one of the multiple optical imaging systems provides both illumination and imaging through a single aperture in the surface of the monitoring plate.

Abstract: Methods, systems, and products help users recall memories and search for content of those memories. When a user cannot recall a memory, the user is prompted with questions to help recall the memory. As the user answers the questions, a virtual recollection of the memory is synthesized from the answers to the questions. When the user is satisfied with the virtual recollection of the memory, a database of content may be searched for the virtual recollection of the memory. Video data, for example, may be retrieved that matches the virtual recollection of the memory. The video data is thus historical data documenting past events.

Abstract: A method for subcutaneously treating pain in a patient includes first providing a neurostimulator with an IPG body and at least a primary, a secondary, and a tertiary integral lead with electrodes disposed thereon. A primary incision is opened to expose the subcutaneous region below the dermis in a selected portion of the body. A pocket is then opened for the IPG through the primary incision and the integral leads are inserted through the primary incision and routed subcutaneously to desired nerve regions along desired paths. The IPG is disposed in the pocket through the primary incision. The primary incision is then closed and the IPG and the electrodes activated to provide localized stimulation to the desired nerve regions and at least three of the nerves associated therewith to achieve a desired pain reduction response from the patient.

Abstract: The present disclosure is directed to systems and methods for identifying demographic information in a data file. The method may include: receiving the data file containing a plurality of fields of demographic information from a third-party, the data file having inconsistent or mislabeled nomenclatures for one or more fields of the plurality of fields or spurious demographic information; analyzing the data file using a machine learning model trained according to other data files to distinguish between each of the plurality of fields of demographic information, the machine learning model being based on a plurality of machine learning algorithms to identify different types demographic information; generating a score indicating a probability that each of the plurality of fields of demographic information was identified correctly; and generating a revised data file labeling each of the plurality of fields of demographic information based on the identified type.

Abstract: An implantable head-mounted unibody peripheral neurostimulation system is provided for implantation in the head for the purpose of treating chronic head pain, including migraine. The system may include an implantable pulse generator (IPG) from which multiple stimulating leads may extend sufficient to allow for adequate stimulation over multple regions of the head, preferably including the frontal, parietal and occipital regions. A lead may include an extended body, along which may be disposed a plurality of surface metal electrodes, which may be sub-divided into a plurality of electrode arrays. A plurality of internal metal wires may run a portion of its length and connect the IPG's internal circuit to the surface metal electrodes. The IPG may include a rechargeable battery, an antenna, and an application specific integrated circuit. The IPG may be capable of functional connection with an external radiofrequency unit for purposes that may include recharging, diagnostic evaluation, and programming.

Abstract: Improved non-cellular (e.g., Wi-Fi) link integration with a cellular (e.g., LTE) network is described. The improved link integration can relate to utilizing an eNodeB device (e.g., residing in a radio access network portion of a cellular network) as an anchor point rather than a packet data network gateway device (e.g., residing in a core network portion of the cellular network) utilized by other approaches. The improved link integration can maintain full compliance with or support for other approaches, and can reduce signaling overhead, simplify quality-of-service management, and/or provide a more rapid reaction to changes of access, particularly in cases where the eNodeB device and a non-cellular access point device are co-located.

Abstract: The present disclosure is directed to systems and methods for identifying demographic information in a marked up document. The method may include: detecting a plurality of fields representing demographic information in a marked up document; extracting a set of features based the detected demographic information; based at least in part on the set of features, determining whether the plurality of fields represent demographic information of a single provider using a machine learning model trained according to other marked up documents; and when the plurality of fields are determined to represent demographic information of a single provider, associating the plurality of fields to represent demographic information of the single provider.

Abstract: The present disclosure is directed to systems and methods for identifying demographic information in a data file. The method may include: receiving the data file containing a plurality of fields of demographic information from a third-party, the data file having inconsistent or mislabeled nomenclatures for one or more fields of the plurality of fields or spurious demographic information; analyzing the data file using a machine learning model trained according to other data files to distinguish between each of the plurality of fields of demographic information, the machine learning model being based on a plurality of machine learning algorithms to identify different types demographic information; generating a score indicating a probability that each of the plurality of fields of demographic information was identified correctly; and generating a revised data file labeling each of the plurality of fields of demographic information based on the identified type.

Abstract: The present disclosure is directed to systems and methods for extracting unstructured data from a data source in a structure manner. Embodiments provide ways to retrieve unstructured data along from data sources not optimized for automated retrieval. For example, embodiments may generate a branched tree for each data source that maps out paths to individual sites of, for example, a healthcare provider listing the unstructured data. Using this branched tree, tasks can be generated to navigate along a path with the data source to each site and extract the unstructured data from the data source. In this way, embodiments provide the ability to navigate through a site from a base site to a site that has the relevant data.

Abstract: To train models, training data is needed. As personal data changes over time, the training data can get stale, obviating its usefulness in training the model. Embodiments deal with this by developing a database with a running log specifying how each person's data changes at the time. When data is ingested, it may not be normalized. To deal with this, embodiments clean the data to ensure the ingested data fields are normalized. Finally, the various tasks needed to train the model and solve for accuracy of personal data can quickly become cumbersome to a computing device. They can conflict with one another and compete inefficiently for computing resources, such as processor power and memory capacity. To deal with these issues, a scheduler is employed to queue the various tasks involved.

Abstract: Disclosed herein are system, method, and computer program product embodiments for performing a regression analysis on lawfully collected personal data records. The analysis enables discovery of individuals likely to perform certain actions based on their personal data records and the personal data records and actions of others. The disclosed system, method, and computer program product may process vast quantities of data, including personal data records with thousands of categories and lawfully stored databases with millions of personal data records. Through the regression analysis, the disclosed system, method, and computer program product learn the most relevant categories for predicting an individual's actions based on input data provided by a user. The analysis then analyzes the categories of personal data records stored in a lawfully stored database to predict actions of individuals associated with those records and outputs results to the user.