Abstract: This document presents devices, systems, and their methods of use for authenticating, evaluating, adjusting, and/or submitting a claim to a third-party obligator. The system may include a client computing device such as a cellular phone, having a downloadable application running thereon. The application running on the client computing device may be configured for generating an interface into which a characterization of treatment to be provided from a healthcare provider to a patient having a third party obligation agreement may be entered, where the obligation agreement includes terms defining coverage for treatments to be provided that will be covered by the agreement. As such, the system may be used to generate a claims submittal packet on behalf of the health care provider for reimbursement from the third party obligator for the treatments provided to the patient by the healthcare provider.

Abstract: An information processing apparatus according to an exemplary embodiment includes a likelihood acquisition unit, a first evaluation unit, a determination unit, and a second evaluation unit. The likelihood acquisition unit is configured to acquire class likelihood for first medical data given a correct answer label, by using a first classifier for classifying medical data. The first evaluation unit is configured to evaluates a degree of deviance based on the class likelihood acquired by the likelihood acquisition unit and a class answer corresponding to the correct answer label. The determination unit is configured to determine whether the degree of deviance by the first evaluation unit satisfies a predetermined criterion. The second evaluation unit is configured to, based on second medical data satisfying the predetermined criterion, out of the first medical data, evaluate a similarity between the second medical data and third medical data to be subjected to classification.

Abstract: Systems and methods are provided for automating the process of automatically determining appropriateness of surgical team services performed during a medical procedure. Clinical resource data with known surgical guideline indicator (SGIs) may be us used to generate and store a mapping of medical procedure codes to indications of the appropriateness of surgical team services corresponding to the medical procedure codes. A medical bill associated with an insurance claim may be analyzed to extract a medical procedure code corresponding to a surgical procedure, and an automated adjudication recommendation for the medical bill may be made based on the mapping between medical procedure codes and SGIs.

Abstract: A system for supporting on the use of an injection device includes a display and a processor configured to determine the injection device, to obtain data on use of the determined injection device and to add at least one overlay on the display, wherein the at least one overlay is generated depending on the obtained data on use of the determined injection device. The processor is configured to adapt the at least one overlay depending on a context of application of the injection device, the context of application of the injection device including at least one of the following: ambient light; time; date; temperature; use history of the injection device; drug; injection site; dosage.

Abstract: Systems and methods for tracking activities from a plurality of multimodal inputs are described. Activity tracking can include receiving a plurality of multimodal inputs, synchronizing the plurality of multimodal inputs, generating segments from the synchronized multimodal inputs, recognizing activities associated with each generated segment by performing a bagged formal concept analysis (BFCA), and recording the recognized activities in a storage. Tracking of activities can include the detection of moments (e.g., eating moments), during which an activity tracking application can prompt a user for information (e.g., a food journal).

Abstract: In one embodiment, a medical data processing apparatus includes processing circuitry. The processing circuitry obtains medical data relating to a subject, and outputs medical diagnostic image data obtained by performing predetermined processing on the medical data, along with standardized medical image data based on the medical data, the standardized medical image data being standardized for machine learning without performing part or all of the predetermined processing.

Abstract: Cohort definition and selection system for a computer having a memory, a central processing unit and a display, the system including: a cohort definition module to configure the memory according to a phenotype vector. The phenotype vector includes a patient ID to uniquely associate the phenotype vector to a patient, a plurality of demographic dimension fields, each demographic dimension field to describe a respective demographic aspect of the patient, a calculated dimension field to describe a calculated information related to the patient, a plurality of phenotype-based dimension fields, each phenotype-based dimension field to indicate relevance of the respective phenotype-based dimension field to the patient, and a child phenotype vector to recursively define a phenotype-based dimension field, and a cohort selection module to select a set of phenotype vectors that are within a predetermined error from a cohort selection criteria.

Abstract: A caregiver user interface displays information from a patient's electronic medical record. The interface associates medical records together that include a common data item. The interface also displays information about data items, such as the status of a data item in an associated historical record. Controls can be displayed in the user interface, which are linked to the historical records.

Abstract: The present disclosure provides monitoring system, device and computed-implemented method for monitoring pressure ulcers. The monitoring system and the device are configured to: capture at least one image corresponding to a user; retrieve the anamnesis data of the user; and determine a pressure ulcers condition result corresponding to the at least one image and the anamnesis data according a pressure ulcers prediction model.

Abstract: A method is provided for lowering blood sugar in a subject in need thereof by administering a biguanide anti-hyperglycemic pharmaceutical composition to a subject qualified for over-the-counter access to the biguanide anti-hyperglycemic pharmaceutical composition. In some embodiments, the biguanide anti-hyperglycemic pharmaceutical composition includes N,N-dimethylimidodicarbonimidic diamide, or a pharmaceutically acceptable salt thereof. In some embodiments, the biguanide anti-hyperglycemic pharmaceutical composition includes metformin hydrochloride.

Abstract: A method is provided for lowering blood sugar in a subject in need thereof by administering a gliflozin Sodium-Glucose Cotransport 2 inhibitor pharmaceutical composition to a subject qualified for over-the-counter access to the gliflozin Sodium-Glucose Cotransport 2 inhibitor pharmaceutical composition. In some embodiments, the gliflozin Sodium-Glucose Cotransport 2 inhibitor pharmaceutical composition includes empagliflozin, canagliflozin, and ertugliflozin. In some embodiments, the gliflozin Sodium-Glucose Cotransport 2 inhibitor pharmaceutical composition includes (2S,3R,4R,5S,6R)-2-[4-chloro-3-[(4-ethoxyphenyl)methyl]phenyl]-6-(hydroxymethyl)oxane-3,4,5-triol or a pharmaceutically acceptable salt thereof.

Abstract: A method for generating synthetic training records for use in training a model to predict low-incidence events. A synthetic training record is generated from a minority-class training record by substituting a different value for a feature in the minority-class training record, where the probability of the different value occurring in the minority-class training record exceeds a probability threshold. Also disclosed are a non-transitory storage medium comprising minority-class training records and synthetic training records and a method of training a machine-leaning model using training records augmented with synthetic training records. An exemplary synthetic training records is a synthetic medical record for use in training a model to predict drug overdoses.

Abstract: Embodiments described herein disclose technology for detecting and mitigating a health event. The system can monitor health information associated with the user. The health information can be collected by sensors. The system can assess the environment in the location of the user using one or more connected devices and/or sensors. Based on the health information and the environment, the system can detect whether a health event is occurring. In response to detecting a health event, the system can generate a mitigation plan and alter controllable environmental features according to the mitigation plan via the connected devices.

Abstract: A modular ACD system is configured to automate clinical documentation and includes a machine vision system configured to obtain machine vision encounter information concerning a patient encounter. An audio recording system is configured to obtain audio encounter information concerning the patient encounter. A compute system is configured to receive the machine vision encounter information and the audio encounter information.

Abstract: A method and system for determining a recommendation for drug treatment are described herein. For example, the method includes determining drug scores based upon network-based distances for one or more target drug nodes, modeling one or more outputs based upon input data, wherein the input data comprises at least a portion of the drug scores, selecting an algorithmic output from the one or more modeling outputs based upon at least one performance criteria, determining if the selected algorithmic output of the modeling satisfies a threshold, and if the selected algorithmic output satisfies the threshold, generating the recommendation for drug treatment. The system includes a processing device and computer readable medium including programming instructions that, when executed, cause the processing device to perform the method as described herein.

Abstract: Healthcare services can be automated utilizing a system that recognizes at least one characteristic of a patient based on images of the patient acquired by an image capturing device. Relying on information extracted from these images, the system may automate multiple aspects of a medical procedure such as patient identification and verification, positioning, diagnosis and/or treatment planning using artificial intelligence or machine learning techniques. By automating these operations, healthcare services can be provided remotely and/or with minimum physical contact between the patient and a medical professional.

Abstract: An operating method for a medical system for performing a surgical procedure, where the medical system includes at least one artificial intelligence, an intraoperative artificial intelligence and an output unit. The operating method including: supplying the intraoperative artificial intelligence with preoperative output data and intraoperative data; processing the preoperative output data and the intraoperative data by the intraoperative artificial intelligence; and outputting output data from the intraoperative artificial intelligence to the output unit that provides a user output based on the output data from the intraoperative artificial intelligence.

Abstract: The system brings together patient data both clinical records and imaging studies from disparate sources to the user workstation or mobile device in real-time and on-demand. In order to do so, the system needs to establish application layer connectivity utilizing HL7 or FHIR and DICOM for imaging. Once a secure connection is established, the system is able to search and retrieve records and present it to end user.

Abstract: A system and method for assigning assessment tasks includes determining tasks in need of completion, where the tasks include assessing a set of documents containing medical patient data and providing a judgment (e.g., classification or label) based on the contents of the document. A process also includes selecting one or more reviewers based on the one or more tasks and providing one or more documents from the set of documents to each of the selected one or more reviewers for completion of the one or more tasks. The process further includes receiving a result of the one or more tasks after completion by the selected one or more reviewers and storing the result in an electronic medical record database.