Abstract: The system captures portions of a label on a package in a set of images, reconstructs the label based on the set of images, identifies text in the label, determines associations of identified text and types of information, and stores the set of images, the reconstructed label, the identified text in the label, and the determined associations as, for example, a batch in a review queue. During a review process, the batch is reviewed and a structured prescription record is determined for the batch which is further used by the system and user of the system associated with the batch to provide various features to the user.

Abstract: A method and system for storing user application programs and micro-service programs, for each of multiple patients that have cancerous cells and receive treatment, includes obtaining clinical records data in original forms, storing it in a semi-structured first database, generating sequencing data for the patient's cancerous and normal cells using a next generation genomic sequencer, storing the sequencing data in the first database, shaping at least some of the first database data to generate system structured data optimized for searching and including clinical record data, storing the structured data in a second database, for each user application program, selecting an application-specific subset of data from the second database and storing it in a structure optimized for application program interfacing in a third database, wherein an orchestration manager operatively connected to one or more micro-service programs receives status messages and initiates a respective micro-service program when program prere

Abstract: A method of performing a surgical procedure includes storing a software application on a memory associated with a computer, which when executed by a processor causes the software application to develop a model of a patient's anatomical structure, process images of the patient's anatomy, display the images of the patient's anatomy on a user interface associated with the computer, superimpose critical structures within the patient over the displayed images of the patient's anatomy, determine a location within the patient's body cavity where the images of the patient's anatomy were taken, and display the model of the patient's anatomical structure on the user interface, the displayed model indicating the determined location where the images of the patient's anatomy were taken.

Abstract: The system captures portions of a label on a package in a set of images, reconstructs the label based on the set of images, identifies text in the label, determines associations of identified text and types of information, and stores the set of images, the reconstructed label, the identified text in the label, and the determined associations as, for example, a batch in a review queue. During a review process, the batch is reviewed and a structured prescription record is determined for the batch which is further used by the system and user of the system associated with the batch to provide various features to the user.

Abstract: Systems and methods may use healthcare protocols for use with distributed ledger technology. The healthcare protocols may be used to, among other things, classify event data items as distributed ledger data items such that record of such classified event data items may be stored in a distributed ledger. Further, the healthcare protocols may be modified over time, and record of such modifications may also be stored in a distributed ledger.

Abstract: A method of determining the risk of developing a known disease or condition or of identifying the presence of the known disease or condition in a subject includes obtaining subject data that includes results of blood tests. The blood tests include a basic metabolic panel (BMP) and a complete blood count (CBC) panel. The method further includes classifying the subject data with respect to the risk of the subject having or developing the known disease or condition by using the subject data in a machine learning classification system. The classification system includes a machine learning model previously trained on BMP and CBC data from a positive group of training subjects who received a diagnosis of the disease or condition and from a negative group of training subjects who were not diagnosed to have the disease or condition.

Abstract: A clinical data interface device provides integrated portions of the electronic medical record system to identify and confirm a patient file for receiving data and personality modules for receiving and translating data from a variety of clinical device monitors for that identified patient.

Abstract: Disclosed is a method for setting authority for use of a brain stimulation device and a device implementing the same, and the method for setting authority for use of a brain stimulation device according to the present disclosure comprises the steps in which: a communication unit of a personal communication device receives, from a server device, a time token for which the authority for use of the brain stimulation device is set; the communication unit transmits the time token to the brain stimulation device or the server device; and after a time corresponding to the usage time of the brain stimulation device stored in the time token has elapsed, the communication unit receives, from the brain stimulation device or the server device, a message to delete the time token or to change the value of a specific field of the time token.

Abstract: Embodiments of the present invention are directed to physiological sensing in a wearable device. Aspects include generating a multi-faceted feedback for a user. Generating the multi-faceted feedback includes generating a baseline physiological sampling schedule for a user, generating a quality-aware feedback of the user, generating a user-state-aware feedback of the user, and generating a context-aware feedback of the user. Aspects also include generating an adjusted physiological sampling schedule for the user based at least in part upon the multi-faceted feedback.

Abstract: A model-assisted system for predicting survivability of a patient may include at least one processor. The processor may be programmed to access a database storing a medical record for the patient. The medical record may include at least one of structured and unstructured information relative to the patient and may lack a structured patient ECOG score. The processor may be further programmed to analyze at least one of the structured and unstructured information relative to the patient; based on the analysis, and in the absence of a structured ECOG score, generate a performance status prediction for the patient; and provide an output indicative of the predicted performance status. The analysis of at least one of the structured and unstructured information and the generation of the predicted performance status may be performed by at least one of a trained machine learning model or a natural language processing algorithm.

Abstract: Providing healthcare services based on the combination of data from electronic healthcare records (EHRs) and community patient data includes: retrieving EHR data from an EHR database for a patient; retrieving community patient data for the patient; and providing clinical decision support for a healthcare provider at a computing device of the healthcare provider by interjecting, into a clinical workflow that utilizes the retrieved EHR data, the retrieved community patient data such that the clinical workflow utilizes the retrieved EHR data and the retrieved community patient data without importing the retrieved community patient data into the EHR database, and providing results of the workflow to the healthcare provider in a user interface at the computing device. The EHR data joined with the community patient data is actionable without importing the community patient data into the EHR database.

Abstract: Solid waste, for example source separated organics (SSO) or commercial and industrial (C&I) waste or both, are treated by first pressurizing the waste against a screen to produce a solids fraction and a liquid fraction. The liquid fraction can be treated in an anaerobic digester. The solids fraction is pulverized or milled, for example with a hammer mill, preferably after being diluted. The pulverized or milled waste is separated again to provide a second solids faction and a second liquid fraction. The liquid fraction can be treated in an anaerobic digester. The solids fraction is primarily inert and can be landfilled, preferably after being washed.

Abstract: A computer-implemented method for expediting processing of a payment for a patient's healthcare service with a healthcare provider includes displaying an out-of-pocket cost for a patient for a healthcare service at a display interface of a computer device prior to the healthcare service being rendered. After patient selection of the healthcare service and payment of any out-of-pocket costs, a health token is issued to the patient as cryptocurrency for payment of the healthcare service. The health token is received from the healthcare provider after the healthcare provider renders the healthcare service, receives the health token from the patient for payment of the healthcare service, and embeds data pertaining to the healthcare service into the health token. Based on the data embedded in the health token, the healthcare service is approved or disapproved. If the healthcare service is approved, a payment for the healthcare service is issued to the healthcare provider.

Abstract: Systems and methods for biometrically identifying an individual via a screening system for screening a subject for a response to neurophysiological stimuli as an indication for COVID-19, wherein the screening system is configured to capture biometric data associated with the subject during screening of the subject. The systems and methods provide the subject a neurophysiological stimulus selected for clinical manifestations of COVID-19, updating biometric template as necessary for individuals, and then determining whether an individual is the subject based on the updated biometric template and a response exhibited by the subject to the neurophysiological stimulus.

Abstract: The present technology calculates a value of future adherence (VFA) score which is a patient-level, predicted, expected cost of conversion from non-adherence to adherence over a specified time-frame. The score consists of three general components: (1) probability of being non-adherent, (2) cost reduction associated with being adherent, and (3) probability of converting from non-adherent to adherent. These values can be combined to create an overall VFA score. A user interface is then provided which shows at least a list of patients and information related to the VFA score.

Abstract: Systems and methods are provided for determining and communicating patient incentive information to a prescriber. The patient incentive information may adjust the patient copay amount for a prescribed medication. The patient incentive information may be determined by evaluating pharmacy identification information and medication identifiers in a received prescription benefit check transaction and/or adjudicated response to a healthcare transaction to determine if an incentive is available to be applied to the current transaction. The incentive amount may be retrieved and the patient copay amount in the adjudicated response may be amended prior to transmitting the adjudicated response to the prescriber of the medication.

Abstract: A computing system can implement a health verification and prediction service by generating an interactive user interface through which users can provide responses to health assertions in one or more trivia sessions. Each of the health assertions can include a correlation value to actual health outcomes based on responses received from individuals a control group and the known health outcomes of those individuals. Based on the responses from the user, the computing system can generate a health profile for the user.

Abstract: Systems and methods for formulating a personalized skincare product for a user. Data inputs reflecting dermal information of the user (e.g., hydration level measurements, oil level measurements, and a photograph of the user's skin reflecting a set of skin concerns) are collected by a computing device and used to determine a set of normalized scores. A skin health data set is generated based on the normalized scores and stored in memory. A skin health metric is determined based on the skin health data set and is stored in memory. The computing device determines, using a machine learning framework, one or more first skincare product formulations based on the user skin health data set. The formulation(s) can be used to manufacture one or more customized skincare products for the user and can be iteratively refined over time, e.g., by collecting additional data from the user over time.

Abstract: A computing system can execute a correlation model for a library of health assertions to configure a correlation value for each health assertion. The correlation value comprises a correlation between knowledge associated with the health assertion and known health outcomes of individuals in a control group who have also provided responses to the health assertions. The computing system provides a health trivia session for users and based at least in part on the performance of the user, generates a morbidity risk profile that is used to classify the user in an underwriting class.

Abstract: Systems and methods for evaluating insulin medicament dosage regimen adherence by a subject are provided. A description of metabolic events the subject engaged in is obtained. Each event comprises a timestamp and a classification that is one of insulin regimen adherent and insulin regimen nonadherent. Events are binned into consecutive time windows on the basis of time to obtain a plurality of subsets. Adherence values are computed. Each adherence value is for a subset and is computed by dividing the insulin regimen adherent events by the total number of events in the subset. Adherence values are combined into a composite value by a process that comprises downweighting a first adherence value, representing a first time window, with respect to a second adherence value, representing a second time window, when the first time window occurs in time before the second time window. The composite value is communicated as a single representation.