Abstract: A method (300) for identifying a characteristic of a user of a personal care device (10) comprising a sensor (28), a controller (30), and a database (34), comprising the steps of: training (320) the device with training data, comprising the steps of: (i) obtaining (322) sensor data for at least one personal care session for each of at least two different users; (ii) extracting (324), via an extraction module, a plurality of features from each of the personal care sessions; and (iii) training (328), using the extracted features, a classifier to identify a characteristic of each of the at least two different users of the device; obtaining (330) sensor data for at least part of a new personal care session; extracting (340) a plurality of features from the sensor data for the new personal care session; and identifying (360), using the trained classifier, a characteristic of the user of the device.

Abstract: A method for healthcare revenue cycle management is disclosed, and includes receiving a transaction proposal at a first peer within a permissioned blockchain network (PBN). The transaction proposal includes a patient identity and a query, the query being a determination of unknown value to be made by a second organization of a plurality of organizations. Each organization of the plurality represents, within the PBN, one of a healthcare payer and a healthcare provider. The method also includes identifying a smart contract associated with the query and defined to automatically adjudicate the query. The method also includes invoking the smart contract in at least one endorsing peer, and receiving, from each endorsing peer, a proposed transaction response. The method further includes automatically adjudicating the query by executing chaincode on a second peer, operating on the required information to assign a value to the determination, then updating the immutable ledger.

Abstract: Systems and methods for implementing machine-learning models for ovarian stimulation is described herein. In some variations, a computer-implemented method may include optimizing an ovarian stimulation process may include receiving patient-specific data associated with a patient, and predicting an egg outcome for the patient for each of a plurality of treatment options for an ovarian stimulation process based on at least one predictive model and the patient-specific data, where the at least one predictive model is trained using prior patient-specific data associated with a plurality of prior patients.

Abstract: A system for generating a parasitic infection nutrition program including a computing device configured to receive at least a parasitic biomarker, generate a parasitic disease assessment referring to a first parasitic infection as a function of the at least a parasitic biomarker, determine a current position of the user, identify, using the current position and the parasitic disease assessment, a parasitic infection intervention, receive a geophysical indicator relating to the user, identify, using the geophysical indicator, a parasitic prevention strategy regarding a second parasitic infection, and generate a parasitic infection nutrition program, using the parasitic infection intervention and the parasitic prevention strategy.

Abstract: The present invention, in some embodiments thereof, relates to a pharmaceutical dispensing system with dynamic and automatic pharmaceutical dispensing regimes and methods thereof.

Abstract: Systems and methods for utilizing machine learning to generate a trans-diagnostic classifier that is operative to concurrently diagnose a plurality of different mental health disorders using a single trans-diagnostic questionnaire that includes a plurality of questions (e.g., 17 questions). Machine learning techniques are used to process labeled training data to build statistical models that include trans-diagnostic item-level questions as features to create a screen to classify groups of subjects as either healthy or as possibly having a mental health disorder. A subset of questions are selected from the multiple self-administered mental health questionnaires and used to autonomously screen subjects across multiple mental health disorders without physician involvement, optionally remotely and repeatedly, in a short amount of time.

Abstract: Monitoring devices monitor physiological parameters of a patient undergoing surgery. The physiological parameters describe a physiological condition of the patient. A processor matches the physiological parameters to stored surgical data associated with adverse surgical events associated with surgical procedures matching the surgery. The processor determines a predicted time at which the physiological condition of the patient will meet a threshold physiological condition associated with the adverse surgical event based on a rate of change of the physiological parameters. Responsive to determining the predicted time, the processor transmits a first alert to robotic surgical controls to adjust the surgery prior to the predicted time. The processor determines that the physiological condition of the patient has met the threshold physiological condition. The processor transmits a second alert to the robotic surgical controls to terminate the surgery.

Abstract: A system and method for analyzing a data store of de-identified patient data to generate one or more dynamic user interfaces usable to predict an expected response of a particular patient population or cohort when provided with a certain treatment. The automated analysis of patterns occurring in patient clinical, molecular, phenotypic, and response data, as facilitated by the various user interfaces, provides an efficient, intuitive way for clinicians to evaluate large data sets to aid in the potential discovery of insights of therapeutic significance.

Abstract: There is provided a method comprising: mapping patient-specific medications (mapped to active ingredients) and patient-specific parameters of a patient to a mapping data-structure that maps between medications, predicted medical outcomes, and patient parameters, each relationship-mapping includes one medication (active ingredient), one predicted medical outcome, one patient parameter, one risk score, a predicted medical outcome(s) denoting a medication induced event of a corresponding mapped medication, the patient parameter(s) including: a medication influencing factor (for an active ingredient, selected from primary parameters affecting the corresponding mapped medication: blood level, absorption, distribution, metabolism, elimination) directly affecting the corresponding mapped medication which affects the medication induced event, and/or an event influencing factor directly affecting the medication induced event, and computing an aggregated risk score for each respective predicted medical outcome by aggre

Abstract: Medical devices and related patient management systems and methods are provided. An exemplary system includes a medical device to obtain measurement values for a physiological condition in a body of a patient and a computing device to identify a plurality of event patterns within a plurality of monitoring periods based on the measurement values, prioritize the plurality of event patterns based on one or more prioritization criteria, filter the prioritized list of event patterns based on one or more filtering criteria, and generate a snapshot graphical user interface display. The snapshot graphical user interface display includes a graph overlay region having a graphical representation of the measurement values with respect to a time of day and an event detection region below the graph overlay region, where the event detection region includes pattern guidance displays for event patterns of the filtered prioritized list ordered according to the prioritization.

Abstract: Device for blood container processing having a data storage reader unit 20 being adapted to read an blood donator identifier from a data storage of a blood container, and a data processing unit 50 being adapted to request for blood donator related information from an data base 163 based on the read blood donator identifier to allow a correct processing of all relevant information with respect to a blood donator and a blood recipient, to match the blood correctly and to avoid any serious injuries on the blood recipient side.

Abstract: A medical scan assisted review system is operable to receive, via a network, a medical scan for review. Abnormality data is generated by identifying a plurality of abnormalities in the medical scan by utilizing a computer vision model that is trained on a plurality of training medical scans. The abnormality data includes location data and classification data for each of the plurality of abnormalities. Text describing each of the plurality of abnormalities is generated based on the abnormality data. The abnormality data and the text is transmitted to a client device. A display device associated with the client device displays the abnormality data in conjunction with the medical scan via an interactive interface, and the display device further displays the text via the interactive interface.

Abstract: A method and system for conducting genomic sequencing, the method comprising storing a set of user application programs wherein each of the programs requires an application specific subset of data, for each of a plurality of patients that have cancerous cells and that receive cancer treatment, obtaining clinical records data in original forms including cancer state information, treatment types and treatment efficacy information, storing the clinical records data in a semi-structured first database, for each patient, using a genomic sequencer to generate genomic sequencing data for the patient's cancerous cells and normal cells, storing the sequencing data in the first database, shaping at least a subset of the first database data to generate system structured data including clinical record data and sequencing data wherein the system structured data is optimized for searching, storing the system structured data in a second database, for each user application program, selecting the application specific subset o

Abstract: An embodiment of the present invention provides a method of creating a classifier indicative of a presence of a medical condition in a subject, comprising receiving chromatogram data indicative of a profile of volatile organic compounds in a sample from each of a first plurality of subjects having the medical condition and a second plurality of subjects without the medical condition, selecting one of the chromatogram data as reference chromatogram data, aligning the remaining chromatogram data in relation to the reference chromatogram data, extracting one or more features from the chromatogram data using a Mexican hat wavelet transform of one or more scales, selecting one or more features of the chromatogram data indicative of the medical condition, and constructing a classifier for determining a boundary between chromatogram data indicative of the medical condition and chromatogram data indicative of an absence of the medical condition.

Abstract: Information about a medical provider's locations, brands, and gateways can be received (e.g., via an online portal). This information can be used to generate a data object that represents relationships between the locations, the brands, and the gateways. This data object can be maintained in a database base that is searchable by a user device. For example, a user of the user device may search the database to identify a medical provider where the user obtains care. Once identified, other systems can be used to connect the user device to a gateway associated with the medical provider in order to download electronic health record data associated with the user.

Abstract: A method comprises displaying, via an interactive interface, a medical scan and a plurality of prompts of each prompt decision tree of a plurality of prompt decision trees in succession, beginning with automatically determined starting prompts of each prompt decision tree, in accordance with corresponding nodes of each prompt decision tree until a leaf node of each prompt decision tree is ultimately selected. Labeling data indicating the ultimately selected leaf node of each prompt decision tree is determined for the medical scan.

Abstract: A computer-implemented method for executing patient management workflows includes acquiring a pre-test dataset of clinically relevant information related to a patient and using a first intelligent agent to identify a diagnostic test for the patient based on the pre-test dataset. Following performance of the diagnostic test, a second intelligent agent is used to select a processing technique to be applied to data collected from the diagnostic test to obtain a diagnostic marker. Following application of the processing technique to the data collected from the diagnostic test, a third intelligent agent is used to generate an optimal patient management plan based on the pre-test dataset, the data collected from the diagnostic test, and the diagnostic marker.

Abstract: A user profile scoring platform may analyze a transaction log of a transaction account of a user to determine, based on transactions of the transaction log, a qualification status of the user, wherein the qualification status indicates that a characteristic of the user satisfies a threshold qualification metric. The user profile scoring platform may determine, based on the qualification status, a transaction-based score associated with the user, wherein the transaction-based score is determined using a transaction log analysis model. The user profile scoring platform may obtain, based on receiving the access information, a user score associated with a user transaction history that is associated with a plurality of transaction accounts that are associated with the user and different from the transaction account. The user profile scoring platform may perform an action based on the transaction-based score and the user score.

Abstract: Various systems, mediums, and methods may involve a bridge configured to communicate with a number of sites, such as fuel sites and/or restaurant sites. For example, a system may determine a mobile device is associated with a given fuel site, possibly located at the given fuel site, among a number of other fuel sites. Further, the system may determine one or more connections of the bridge that may be configured to communicate with a site component of the fuel site. As such, the system may transmit fuel data to the mobile device based on the one or more connections with the site component. Thus, the mobile device may display an indication of fuel available at the fuel site.

Abstract: A balance and control system may write a data file transfer confirmation from a transmitter system to a blockchain in response to the transmitter system transmitting a data file to a receiver system with the confirmation including a transmitter system address, a receiver system address, and a first hash of the data file. The system may also write a data file transfer acknowledgement from a receiver system to the blockchain with the acknowledgement including the transmitter system address, the receiver system address, and a second hash of the data file. The blockchain may execute a smart contract to compare the first hash of the data file to the second hash of the data file to identify an out-of-balance file transfer event. A monitoring device of the B&C system may read the out-of-balance file transfer event from the blockchain.