Abstract: A system and method for updating patient devices is disclosed. The patient devices may include respiratory therapy devices that operate in accordance with instruction sets, such as software or firmware. A server may maintain a database of configuration data indicating the versions of the software and firmware that is currently installed on the patient devices. The server may also transmit updated instructions from over a network, including a wireless network. Particular patient devices may be selected for updating based on the configuration data. Upon performing an update a patient device may transmit configuration data to the server.

Abstract: A method, apparatus and computer program product provide for monitoring an adjudication network. In relation to a method, first information is caused to be provided by a request processor in response to an inquiry to be provided to a source. The method also receives an order including second information, different than the first information, from the source. The method further combines at least some of the second information with at least some of the first information to form an updated order and transmits the updated order to a supplier. Additionally, the method monitors the adjudication network, such as for a predefined period of time, to determine a status of the updated order and provides a notification to the source in response to the updated order having a predefined status.

Abstract: Systems, methods and computer-readable media are provided for facilitating clinical decision support and managing patient population health by health-related entities including caregivers, health care administrators, insurance providers, and patients.

Abstract: Systems and methods may be provided that may enable an individual to retrieve one or more prescription products (e.g., product refills) from a self-service retrieval location such as a counter, drive-thru, drop box, or kiosk. A unique-machine readable code may be associated with a particular one or more prescription products (e.g., associated with a medical prescription of a patient). The unique machine-readable code may be provided to a computing device of the individual, along with an anticipated time of preparedness of the one or more products for retrieval at the retrieval location. Identification of the unique machine-readable code may result in dispensing of the one or more prescription products associated at the retrieval location.

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: Computer network architectures for machine learning, and more specifically, computer network architectures for the automated completion of healthcare claims. Embodiments of the present invention provide computer network architectures for the automated completion of estimated final cost data for claims for healthcare clinical episodes using incomplete data for healthcare insurance claims and costs, known to date. Embodiments may use an automatic claims completion web application, with other computer network architecture components. Embodiments may include a combination of third-party databases to generate estimated final claims for pending patient clinical episodes, and to drive the forecasting models for the same, including social media data, financial data, social-economic data, medical data, search engine data, e-commerce site data, and other databases.

Abstract: System and method for coaching based on workout history. Improved solutions enable intelligent management of a user's personal fitness journey based on workout recommendations that closely align with the user's traits. In one exemplary embodiment, workout data for a population of different individuals is analyzed to identify groups of similarly performing individuals. Each group of individuals is analyzed to generate an expected profile that approximates the physiological and/or psychological traits of the group. An expected profile includes heuristics and/or performance metrics that enable dynamic coaching during workouts. Subsequently thereafter, user's can be dynamically coached by their client device, based on the expected profile.

Abstract: A user-initiated request from a user device of a user is detected. The user-initiated request is directed to a product provider, the user-initiated request includes one or more parameters. an anonymized request is created based on the one or more parameters. The anonymized request is sent to the product provider. A provider response is received from the product provider. A targeted response is generated based on the one or more parameters of the user-initiated request and based on the provider response. The targeted response is transmitted to the user device of the user.

Abstract: A system for generating a nourishment program includes a computing device configured to retrieve a nociception parameter, classify the nociception parameter to a nociception grouping, identify, using the nociception grouping, a plurality of nutrition elements, wherein identifying the plurality of nutrition elements includes generating a plurality of nutritional metrics associated with reduction of nociception as a function of the nociception grouping, determining a respective effect of each nutritional metric of the plurality of nutritional metrics on the nociception parameter, calculating at least a nutritional level as a function of the respective effect of each nutritional metric, wherein the at least a nutritional level comprises an amount intended to address the nociception parameter, and identifying the plurality of nutrition elements as a function of the at least a nutritional level, and generate a nociception nourishment program using the plurality of nutrition elements.

Abstract: An example method comprises: performing a first intraoral scan of an oral cavity, the oral cavity including a dentition of a patient; identifying a first digital representation of dental anatomy associated with the dentition of the patient; causing the first digital representation of dental anatomy to be stored at an external storage location; appending, to a current data block of a main blockchain, a reference to a first data block of an auxiliary blockchain; appending, to the first data block of the auxiliary blockchain, an identifier of the external storage location; appending, to the current data block of the main blockchain, a first data item of the first digital representation of dental anatomy; appending, to the current data block of the main blockchain, a reference to a preceding data block of the main blockchain; and broadcasting the current data block of the main blockchain to a plurality of blockchain nodes.

Abstract: A personal care device that is capable of two-way communication is provided. In some embodiments, the personal care device operates in a first mode and a second mode depending on whether a signal has been received from a networked computing device, thus allowing a single human-machine interface (HMI) device to both control the personal care device and to cause signals to be sent to the networked computing device. In some embodiments, the personal care device is configured to present media streamed from the networked computing device, and/or to stream audio detected by the personal care device to the networked computing device.

Abstract: Embodiments of the present disclosure provide methods, apparatus, systems, computing devices, computing entities, and/or the like for processing an inclusion of an entity for an event. In accordance with one embodiment, a method is provided that includes: determining whether a graph representation data object comprises an inbound edge connecting an entity node representing the entity with an event node representing the event; and responsive to determining the graph representation data object comprises the inbound edge, performing an action involving inclusion of the entity for the event. The inbound edge is generated via an inbound edge generator machine learning model configured to: traverse entity and/or inclusion edges of the graph representation data object to identify inclusion and entity edges connected, generate an entity score data object for the entity based at least in part on the inclusion edges, and responsive to the data object satisfying a threshold, generate the inbound edge.

Abstract: A computer-implemented method of providing a recommendation as to a fault determination for a motor vehicle collision is disclosed. The method may include receiving unstructured text describing the circumstances of the collision. The unstructured text is evaluated an associated intent related to the circumstances of the motor vehicle collision is identified. The intent is mapped to an internal node of a decision tree corresponding to a set of fault-determination rules. The computer then successively prompts and receive input responsive to the prompting that corresponds to details of the circumstances of the collision. The computer may identify, based on the received input, a path through the decision tree ending at a leaf node that corresponds to a fault-determination rule governing motor vehicle collisions that matches the circumstances of the motor vehicle collision. The recommendation is then provided based on that rule. Related systems and computer-readable media are also disclosed.

Abstract: A computer system selects features of a dataset for predictive modeling. A first set of features that are relevant to outcome are selected from a dataset comprising a plurality of cases and controls. A subset of cases and controls having similar values for the first set of features is identified. The subset is analyzed to select a set of additional features relevant to outcome. A first and second predictive model are evaluated to determine that the second predictive model more accurately predicts outcome, wherein the first predictive model is based on the first set of features and the second predictive model is based on the first set of features and the additional features. The second predictive model is utilized to predict outcomes. Embodiments of the present invention further include a method and program product for selecting features of a dataset for predictive modeling in substantially the same manner described above.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for predicting future patient health using neural networks. One of the methods includes receiving electronic health record data for a patient; generating a respective observation embedding for each of the observations, comprising, for each clinical note: processing the sequence of tokens in the clinical note using a clinical note embedding LSTM to generate a respective token embedding for each of the tokens; and generating the observation embedding for the clinical note from the token embeddings; generating an embedded representation, comprising, for each time window: combining the observation embeddings of observations occurring during the time window to generate a patient record embedding; and processing the embedded representation of the electronic health record data using a prediction recurrent neural network to generate a neural network output that characterizes a future health status of the patient.

Abstract: A method for checking the quality of data content in a structured clinical record is disclosed. The method may include the steps of providing a data quality test that checks the content of at least a portion of the data content in the structured clinical record, applying the data quality test to the portion of the data content, and returning the results of the data quality test.

Abstract: Methods, computer systems, and computer readable media for transforming raw healthcare data into relevant healthcare data are provided. Transformation of raw healthcare data into relevant data is accomplished by receiving raw data from a plurality of disparate data sources, indexing the data, and mapping the data. Embodiments transform raw data into relevant data through the use of natural language processing, synonymy and ontology mapping, and adaptive knowledge processing. The relevant data is stored in a one record that includes information necessary to understand and represent that patient.

Abstract: Networks and methods include receiving healthcare information and with a computer identifying when a patient is readmitted to a healthcare provider. A readmission notification is generated for identified readmissions. The notification may identify the patient being readmitted, the readmitting event, prior event(s) and provider(s), substantive healthcare and clinical status for the patient, treatment dates, and/or any other desired information. Readmission alerts can be formatted and provided in accordance with their consumers' parameters. Example methods and embodiments may receive, process, store, compare, and otherwise use any of HL7 messages, CCDA information, clinical feeds, or any other type of electronic healthcare record. This information may be received from any number of different healthcare information sources and providers.

Abstract: A system to verify the identity of a recipient requesting fulfillment of a prescription for a pharmaceutical product includes a point-of-sale retail personal identification number entry device (pinpad) and a workstation that stop a transaction for the pharmaceutical product from proceeding in response to a request associated with a claim for dispensing the pharmaceutical product. A first input for data identifying a member of a rewards program is entered with the pinpad, and a second input for data identifying a recipient of the prescription is entered with the workstation. The workstation compares the data identifying the member of the rewards program against the data identifying the recipient of the prescription. If there is a match between the data identifying the member of the rewards program and the data identifying the recipient of the prescription, the pinpad and workstation allow the transaction for the pharmaceutical product to proceed.

Abstract: A system for classifying a target image with segments having attributes is provided. The system generates a graph for the target image that includes vertices representing segments of the image and edges representing relationships between the connected vertices. For each vertex, the system generates a subgraph that includes the vertex as a home vertex and neighboring vertices representing segments of the target image within a neighborhood of the segment represented by the home vertex. The system applies an autoencoder to each subgraph to generate latent variables to represent the subgraph. The system applies a machine learning algorithm to a feature vector comprising a universal image representation of the target image that is derived from the generated latent variables of the subgraphs to generate a classification for the target image.

Abstract: The risk analysis system according to the present invention includes: a storage apparatus which stores subject data including information related to health of a subject; an analyzer which analyzes a risk related to the health of the subject based on the subject data acquired from the storage apparatus; and an output apparatus which outputs an analysis result by the analyzer. The analyzer has: a risk estimating unit which estimates an event onset risk of the subject based on the subject data; and a medical expense predicting unit which predicts future medical expenses, which are medical expenses to be incurred in the future by the subject, based on the event onset risk estimated by the risk estimating unit and the subject data.

Abstract: A surgical system, method and CAD program are provided for facilitating surgical planning. A digitization device has a pointer tip and one or more control inputs. A navigation system tracks the digitization device. The CAD program generates a virtual reference frame and receives the tracked state of the digitization device from the navigation system. The CAD program renders, within the virtual reference frame, a virtual representation of the pointer tip of the digitization device having a pose of the pointer tip derived from its tracked state. In response to actuation of the control input(s) of the digitization device, the CAD program registers local virtual reference(s) within the virtual reference frame at a location relative to the pose of the virtual representation of the pointer tip and enables arrangement of geometrical design object(s) within the virtual reference frame relative to the registered local virtual reference(s) to facilitate surgical planning.

Abstract: Data related to the adherence of a patient to a therapy regime can be collected from multiple medical devices, each of which may have an incomplete data set with data entries associated with times. Each incomplete data set represents a portion of a complete data set. The data sets can be integrated to create a complete data set with data entries from each incomplete data set being arranged in a temporal sequence with respect to one another. A report may be generated, the report having the data entries of the complete data set or a function of the data entries of the complete data set.

Abstract: A method, a computer system, and a computer program product for two-way document generation for medical communication are provided. Patient data from a patient may be received. Medical services provider data from a medical services provider may be received. The patient data and the medical services provider data may be run through a machine learning model so that the machine learning model may produce a first document and a second document. The first document may be presented to the patient. The second document may be presented to the medical services provider.

Abstract: In some examples, systems, methods, and devices are described that generate contextual suggestions for patients. Generation of the contextual suggestions is triggered by certain events performed by a medical professional with respect to a patient (e.g., updating a patient record). The contextual suggestions are related to addressing health conditions of the patient and represent tasks or considerations which the medical professional should be made aware. The contextual suggestions are generated in a way that is considerate of patient context, medical professional context, and contexts of similar patients. The contextual suggestions can be presented to the medical professional for selection and execution.

Abstract: The present system and method is directed to a process to facilitate trusted sources of information in an enterprise. The present system and method positions data governance to move away from the element level and focus on the data asset (i.e. repository, interface, subject) level. When data persons are having any issue with their data asset, whether it is a conflicting data asset, interface issues, competing data asset, new data asset build, data subject issue, or the like, a certifier may operate to assess the asset based on our well defined metrics, determine the health through the data asset scoring process, recommend asset services, and provide those services to the data owner who is ultimately responsible for implementing them to improve the data and the data processes.

Abstract: The present invention relates to a method for generating a prediction result for predicting an occurrence of fatal symptoms of a subject in advance, a method for performing data classification by using data augmentation in mechanical learning for the same, and a computing device using the same. Particularly, the computing device according to the present invention acquires vital signs of the subject, converts the same into individuated data, generates analysis information from the individuated data on the basis of a machine learning model, generates a prediction result by referring to the analysis information, and provides the prediction result to an external entity.

Abstract: Methods of treatment and diagnosis using facilitated communication of health information from a patient device to a physician device are provided herein. Methods include improved dissemination and management of health information data while safeguarding patient privacy. A patient may initiate a tele-medicine session for treatment using a portable user device of the patient, after which a physician may request a set of data through the patient device relevant to the treatment. In response, the device of the patient identifies a subset of the data set requested by the physician that is authorized by the patient for release to the physician. The system further facilitates display of differing types of information on a user interface of the physician's device to facilitate improved treatments and diagnostics, health information collection and patient follow-up.

Abstract: In an embodiment, an electronic device includes a display screen, a memory circuit, and computing circuitry, which is coupled to the display screen and to the memory circuit, and which is configured to cause the display screen to display icons that are each related to respective data regarding a patient at a medical facility, to retrieve, from the memory, the respective data in response to a user of the electronic device selecting, via the display screen, a corresponding one of the displayed icons, and to cause the display screen to display the retrieved respective data.

Abstract: A ventilator system is capable of displaying complex information patterns in a GUI, thereby allowing a clinician to get subtract complex information from multiple parameters inputs.

Abstract: A system of medical devices, the system comprising: a medical device data management system; a plurality of medical devices communicatively connected to the medical device data management system; each medical device being operable to analyze one or more samples of biological material; and to communicate information about an operational state of the medical device to the medical device data management system; a plurality of portable electronic devices, each operable to be carried by an operator, each portable electronic device communicatively connectable to the medical device data management system and configured to receive, from the medical device data management system, information indicative of an operational state of respective medical devices and to display the received information in respect of one or more selected ones of the medical devices.

Abstract: A method and system for configuring a computer for data classification using ordinal regression includes: receiving and storing a data set having data with a plurality of data features that have an ordinal relationship; generating a plurality of ordinal classification bins based on the relationship of the data features, at least one ordinal classification bin having walls defined by at least two hyperplanes; generating an ordinal regression model of the data set illustrating the data of the data set arranged into the plurality of ordinal classification bins; and tuning the slopes of the walls of the at least one ordinal classification bin based on the relationships between the plurality of data features of the data arranged within the at least one ordinal classification bin such that the slopes of the two hyperplanes defining the walls of the at least one ordinal classification bin are not parallel.

Abstract: Example methods and systems for quality-aware continuous learning for radiotherapy treatment planning are provided. One example method may comprise: obtaining an artificial intelligence (AI) engine that is trained to perform a radiotherapy treatment planning task. The method may also comprise: based on input data associated with a patient, performing the radiotherapy treatment planning task using the AI engine to generate output data associated with the patient; and obtaining modified output data that includes one or more modifications made by a treatment planner to the output data. The method may further comprise: performing quality evaluation based on (a) first quality indicator data associated with the modified output data, and/or (b) second quality indicator data associated with the treatment planner. In response to a decision to accept, a modified AI engine may be generated by re-training the AI engine based on the modified output data.

Abstract: A system for customizing user parameters relating to a pharmaceutical treatment, receives, a first set of parameters associated with the pharmaceutical treatment, that indicate factors associated with the pharmaceutical treatment, in a first format. The system determines a subset of the set of first parameters based on the one or more factors and converts them into a second format. The system provides the second set of parameters to a second computing device, receives from the second computing device, a third set of parameters, wherein the third set of parameters are based on the one or more factors, the third set of parameters being provided in a third format, converts the third set of parameters from the second third format to the first format based on a second set of parameters, and present the converted third set of parameters received from the second computing device to the first computing device party.

Abstract: Embodiments are directed to an interactive text message based coaching program. A computer system generates customized messages for a first user containing information related to a health-related campaign program. The computer system generates the messages via a user interface in response to user-input provided by a second user. Messages are included in interaction components that include a user-specified link that logically connects the interaction component to another interaction component in a decision tree. The decision tree defines a sequence of messages to be sent to the first user. For example, a next message of the sequence can be based on a response from the first user to a previous message of the sequence.

Abstract: Embodiments for intelligent collaborative generation or enhancement of useful medical actions to a user by a processor. One or more useful medical actions may be recommended, with evidence in support thereof, for positively impacting a health state of a user according to data relating to similar users. One or more of the recommended user medical actions may be matched to one or more selected portions of clinical practice guidelines (CPGs). The one or more of the recommended user medical actions may be added as an additional CPG or as an enhancement to one or more of the matching portions of the recommended user medical actions.

Abstract: According to one method for using machine learning in detecting drug diversion, the method comprises receiving, as input, an observed drug dispensation amount associated with a drug dispensation event related to a drug provider along with other drug dispensation event data, wherein the drug dispensation event data comprises drug provider information, procedure information, and patient information; generating, using a trained drug diversion detection algorithm and the drug dispensation event data, an expected drug dispensation amount associated with the drug dispensation event and determining, using the observed drug dispensation amount and the expected drug dispensation amount, whether the observed drug dispensation amount is aberrant, wherein the drug diversion detection algorithm includes at least one machine learning algorithm and is trained using one or more data sets associated with related drug dispensation events; and outputting, by the drug diversion detection algorithm, information indicating that th

Abstract: A method includes receiving information associated with a stimulus, the information associated with the stimulus comprising first information associated with a medical claim for services provided to a patient and second information associated with a provider that provided the services to the patient; and predicting, using an artificial intelligence engine, when an event will occur in response to the stimulus.

Abstract: A medication inventory system may include a medication tray that includes compartments for storing respective medications. The medication tray may have a tray identifier associated therewith. The system may also include a mobile wireless communications device configured to obtain at least one image of the medication tray, and apply a Hough line detection algorithm to the at least one image to determine a boundary outline of the medication tray. The mobile wireless communications device may also be configured to generate a current medication stocking list of the medication tray based upon the boundary outline and the tray identifier from the at least one image.

Abstract: A medical information navigation engine (“MINE”) includes a medical information interface, a reconciliation engine and an intent-based presentation engine. The medical information interface receives medical information from a plurality of medical sources, which is subsequently reconciled by the reconciliation engine. The intent-based presentation engine clusters the reconciled medical information by applying at least one clustering rule to the reconciled medication information. The clustered reconciled medical information can be presented to a user.

Abstract: An enterprise system and method for maintaining and transitioning humans to a human-like self-reliant entity is presented. Said system including at least one a biological, biomechatronic, and mechatronic entity with a biological or artificial neural network to at least one transform or maintain. Embodiments are provided to assist in the transition of human between a biological state to a bio-mechatronic and mechatronic entity. Said entity's biological, biomechatronic, and mechatronic subsystems are configured to communicate and interact with one another in order for said enterprise system to manage, configure, maintain, and sustain said entity throughout the entity's life-cycle. Subsystem embodiments and components supported by the enterprise system are presented.

Abstract: A patient support apparatus, such as a hospital bed, communicates with an electronic medical record (EMR) system in healthcare facility. The hospital bed includes a patient support structure to support a patient, a graphical user interface coupled to the patient support structure, and control circuitry coupled to the graphical user interface. The graphical user interface displays at least one input that may be used by a caregiver to chart data into an electronic medical record (EMR) of a patient supported by the patient support structure.

Abstract: Methods and architecture for using sensor data to offer content, such as purchase or viewing suggestions, to a viewer, are disclosed. Wearable or other external sensor devices may monitor a viewer while the viewer consumes a first media element. The sensor data may then be used to determine an emotional response of the viewer to the media element or to entities found within that element, such as actors, scenes, brands, or objects. Emotional response data for a user may be stored, and may be used either immediately or at a later time to deliver content or make content or purchase suggestions to the viewer.

Abstract: Disclosed herein are systems and methods for identifying radiation therapy treatment data for different patients, such as field geometry. A central server collects patient data, radiation therapy treatment planning data, clinic-specific rules, and other pertinent treatment/medical data associated with a patient. The server then executes one or more machine-learning computer models to predict field geometry variables and weights associated with the patient's treatments. Using the predicted variables and weights, the server execute a clinic-specific set of logic to identify suggested field geometry, such as couch/gantry angles and/or arc attributes. The server then monitors whether end users (e.g., medical professionals) revise the suggested field geometry and trains the model accordingly.

Abstract: A computer-implemented method reduces an amount of machine health data to be stored in a data storage device while preserving details of extrema values occurring within incremental measurement time intervals in an extended time period during which the data were collected. The method includes: sensing an operational characteristic of a machine and generating an operational characteristic signal; generating machine health parameter data that include amplitude values and associated time values; for each incremental measurement time interval, calculating an average value of the amplitude values, identifying a maximum value of the amplitude values, and identifying a minimum value of the amplitude values; and storing a compressed machine health parameter data set in the data storage device. The compressed machine health parameter data set includes the calculated average values and the identified maximum and minimum values for the incremental measurement time intervals.

Abstract: In some examples, user models are generated to represent experience of users with respect to their roles. Models that represent conditions are also generated. As part of generating a support element for a particular user, a triggering event is detected (e.g., an update to a user record), a condition is identified, a condition model and a user model are compared to identify a condition preparedness score. This score is used to generate the support element, which is shared with a user device of the user.

Abstract: A method for presenting an interactive emergency department (ED) dashboard display for an ED at a user computing device is provided. The method may include presenting a plurality of user interface indicators on the interactive ED dashboard display at the user computing device. Each of the plurality of user interface indicators may correspond to a real-time performance metric for the ED, where the real-time performance metric is based on patient data for a plurality of patients in the ED. A user input may be received at the user computing device. The user input may indicate a selection of one of the plurality of user interface indicators. The method may further include, in response to the user input, presenting on the interactive ED dashboard display the patient data that is associated with the real-time performance metric corresponding to the selected one of the plurality of user interface indicators.

Abstract: Embodiments of the disclosure provide methods, apparatuses, and computer-readable media for generating image reports. In one embodiment, the method includes: obtaining an image to be analyzed; determining at least one reference image corresponding to the image to be analyzed, the at least one reference image corresponding to a respective reference image report; and generating, based on the reference image report, an image report corresponding to the image to be analyzed. In the method for generating an image report provided by the embodiments, by obtaining an image to be analyzed is obtained, at least one reference image corresponding to the image to be analyzed is determined; and an image report corresponding to the image to be analyzed is generated based on a respective reference image report corresponding to the at least one reference image.

Abstract: In an approach to predictive contact tracing, a computer receives a query associated with contact tracing of a person with an infection. A computer retrieves timestamped location data associated with the person over a period of time. Based on the retrieved data, a computer creates a contact graph associated with the person, where the contact graph depicts one or more other people that were in contact with the person over the period of time. A computer retrieves medical data associated with the person and the one or more other people that were in contact with the person over the period of time. Based on the retrieved data, a computer builds a probabilistic model. A computer runs the probabilistic model to provide a prediction of a probability of infection of the one or more other people over the period of time as a result of being in contact with the person.

Abstract: The present solution is generally directed to managing remote procedure calls in centralized processing. In particular, the present solution can reduce the number of remote procedure calls by selecting and applying multiple processing scripts for a single electronic transaction based on a real-time condition.