Abstract: In one example, an ambulatory medical device is provided. The ambulatory medical device includes a plurality of subsystems, at least one sensor configured to acquire data descriptive of a patient, a user interface and at least one processor coupled to the at least one sensor and the user interface. The at least one processor is configured to identify subsystem status information descriptive of an operational status of each subsystem of the plurality of subsystems and to provide a device health report for the ambulatory medical device via the user interface, the device health report being based on the operational status of each subsystem.

Abstract: A method includes: receiving, by a computer device, an association of a prescribed treatment to a user; receiving, by the computer device, an image of the user; receiving, by the computer device, an image of treatment adherence by the user; determining, by the computer device, adherence to the prescribed treatment by analyzing the image of treatment adherence; and generating, by the computer device, a personalized visualization illustrating the determined adherence to the prescribed treatment by modifying the image of the user.

Abstract: Method for removing personal data from a medical record includes receiving a first digital medical record associated with a first patient, the first digital medical record including personal data and medical data; generating a first fingerprint by applying a cryptographic function to at least a portion of the personal data; transferring the first fingerprint to one or more computing devices; identifying a first alias associated with the first fingerprint, wherein identifying the first alias includes at least one of determining that the first fingerprint was previously stored along with the first alias, and generating the first alias and storing the first fingerprint and the first alias; transferring the first alias to the workstation of the first user; and generating a first clean digital medical record based on the first alias and the first digital medical record.

Abstract: Example methods, apparatus and articles of manufacture to process insurance claims using cloud computing are disclosed herein. An example system to process an insurance claim using cloud computing includes an assistance resource of a cloud computing platform configured to interact electronically with at least one of an insured person, a representative of the insured person, or a representative of an insured entity to obtain information related to an insurance claim, an artificial intelligence resource of the cloud computing platform configured to process the information to identify an action to be taken for the insurance claim, and a backend system configured to perform the action, the backend processing module also useable by a person to manually process the insurance claim.

Abstract: An apparatus and a method for monitoring a bio-signal measuring condition are disclosed. The apparatus includes a bio-signal receiver configured to receive a bio-signal that is measured from a user, and a processor configured to extract any one or any combination of a waveform feature, a period feature, and an amplitude feature, from the received bio-signal, determine whether the extracted any one or any combination of the waveform feature, the period feature, and the amplitude feature are normal, using at least one predetermined determination reference corresponding to the extracted any one or any combination of the waveform feature, the period feature, and the amplitude features, and monitor a measuring condition of the received bio-signal, based on whether the extracted any one or any combination of the waveform feature, the period feature, and the amplitude feature are determined to be normal.

Abstract: System for inducing sonoporation of a drug into cancer cells in a tumor and method thereof, the system comprising a generator configured to provide electrical energy at an ultrasound frequency; an ultrasound probe electrically connected to the generator and configured to convert the electrical energy into low intensity pulsed ultrasonic waves defined by operation parameters, said operation parameters comprising the frequency, the duty cycle, the operation time of the ultrasonic waves; an input device enabling an operator to enter configuration data comprising: type of tumor, type of drug, localization of secondary tumor, anthropometric measurements and grade of tumor, and a processor configured to determine the values of the operation parameters on the basis of the entered configuration data and control the generator and the ultrasound probe to operate according to said determined values, wherein the value of the frequency is determined on the basis of the type of tumor, the localization of the tumor, the gra

Abstract: Computer-implemented systems and methods are provided for constructing a numerical model to generate a probability that a patient diagnosed with multiple myeloma will die within a predetermined period of time. Reference data for a plurality of patients diagnosed with multiple myeloma is received. First variables selected from the reference data are deemed predictive of mortality for a first predetermined period of time, and second variables selected from the reference data are deemed predictive of mortality for a second predetermined period of time. A first computer model comprising a combination of variables of the first selected variables and first weighting factors is generated. A second computer model comprising a combination of variables of the second selected variables and second weighting factors is generated. The first computer model and the second computer model are trained using the reference data to determine numerical values for the respective first and second weighting factors.

Abstract: A system for using artificial intelligence to select a compatible element. The system includes at least a server wherein the at least a server is configured to receive training data. The at least a server is configured to receive at least a biological extraction from a user. The at least a server is configured to receive at least a datum of user activity data. The at least a server is configured to select at least a compatible element as a function of the training data, the at least a biological extraction, and the at least a user activity data. The at least a server is configured to transmit the at least a compatible element to a user client device.

Abstract: A method for the computer-assisted implementation of radiology recommendations includes any or all of: receiving a set of inputs; determining and/or identifying a set of findings; determining a set of follow-up recommendations; and triggering a set of outputs and/or actions based on the set of follow-up recommendations. A system for the computer-assisted implementation of radiology recommendations preferably includes and/or interfaces a set of computing subsystems and/or processing subsystems, but can additionally include and/or interface with a set of devices (e.g., user devices), models, and/or any other components.

Abstract: A plurality of attributes are extracted from a plurality of electronic health records, where each electronic health record is associated with a patient in a plurality of patients. Additionally, a training data set and a scoring data set are generated based on the plurality of attributes, and a patient similarity model is trained based on the training data set. A precision cohort is identified, where the precision cohort includes patients in the plurality of patients from the scoring data set that are similar to a first patient based on an electronic health record of the first patient and the similarity model. At least one result statistic for each of a plurality of treatments given to patients in the precision cohort is determined, and a first treatment of the plurality of treatments is selected for the first patient based at least in part on the determined result statistics.

Abstract: The present disclosure provides systems and methods for calibrating medical devices and processing physiological measurements using a medical device management system. As an example, the medical device can be a handheld glucometer configured for invasive testing and non-invasive testing of physiological parameters of a patient.

Abstract: A system for determining a plurality of nutritional needs of a user and generating a nutrient supplementation plan using artificial intelligence includes at least a computing device designed and configured to receive, from a user, at least a biological extraction, generate, using the at least a biological extraction and a first machine-learning process, a plurality of nutritional needs of the user, determine a nutritional input to the user, detect at least a nutrition deficiency as a function of the plurality of nutritional needs and the nutritional input, and calculate at least a supplement dose from the plurality of nutritional needs and at the least a nutrition deficiency.

Abstract: A method for securing sensitive information, includes storing patient information in a secured form in an external device that is carried by a patient. A user terminal obtains a first signature generated using a first secret key inside a first identification medium, where the first secret key is associated with a first healthcare person. Moreover, the user terminal communicates a write request that includes at least the first signature to the external device. The external device receives the write request from the user terminal when the user terminal is within a proximal communication range of the external device. Furthermore, the external device verifies at least the first signature received in the write request. The user terminal writes first information to the external device, based on verification of at least the first signature. A system for securing sensitive information is also provided.

Abstract: A method, computer program product, and computing system for: receiving an initial portion of an encounter record; processing the initial portion of the encounter record to generate initial content for a medical report; receiving one or more additional portions of the encounter record; and processing the one or more additional portions of the encounter record to modify the medical report.

Abstract: A method and system is provided for recording a health care event, optimizing medical procedures and calculating reimbursement. The method includes: acquiring metadata comprising a patient identifier, a practitioner identifier, a health care site identifier, an entry time and a medical reason for the health care event; receiving a reimbursement request; generating a procedures list based on the medical reason; selecting a procedure; generating a list of required data types and a list of required quality data for the procedure; acquiring raw data comprising the procedure, a medical device identifier, an entry time and one or more quality data from the medical device for the procedure; and calculating a reimbursement for the health care event based on the procedure, the medical device identifier, the required quality data and the quality data from the medical device. The method implements iterative learning using the collected data to determine optimal health care procedures.

Abstract: A method, computer program product, and computing system for obtaining encounter information of a patient encounter; processing the encounter information to generate an encounter transcript; and processing the encounter transcript to locate one or more procedural events within the encounter transcript.

Abstract: A medication vending device is provided with at least three distinct vending modes. A first vending mode causes the device to output a prompt at the respective dose time. The prompt communicates to the patient that a dose of medication should be vended from the device by the patient and immediately consumed. A second vending mode causes the device to automatically vend a dose of medication at the respective dose time without requiring any action by the patient. A third vending mode causes the device to immediately vend a dose of medication without requiring any action by the patient. The third vending mode allows for selection of a daily dose time from the plurality of daily dose times, and selection of one or more future dates, so as to cause immediate vending of the medication doses for the selected daily dose time for the selected one or more future dates.

Abstract: The present disclosure provides systems, methods, and kits for collecting health measurement data and processing the health measurement data to generate alerts and modify patient treatment plans. An example system can be configured to (i) receive data defining a plurality of health sensors; and (ii) generate, based on the data, application logic configured to cause, in response to one user input, a user device to: (a) couple to the plurality of health sensors, thereby establishing communication between the user device and each of the plurality of health sensors, and (b) provide instructions to a user of the user device through an interface of the user device. The instructions can comprise instructions for taking health measurements using the plurality of health sensors.

Abstract: A parallel network architecture connects among providers, subscribers, and storage networks to pull clinical records in an automated and verifiable electronic context. Messages, alerts, or data updates from a healthcare event such as a discharge are received, and example embodiment networks calculate patient clinical data target from the same and query the target for the patient to solicit records for the patient of the event, proximate to the event. The received records may be clinical, with diagnostic and treatment records for the patient, to be automatically delivered back to a subscribing user. Example embodiment networks may improve record quality and data match by verifying a target stores records for the patient, timing queries and requested data to those found most successful for a target, and/or not delivering records that contain errors, no clinical data, are duplicative or unreadable, and/or are not for the patient or healthcare event.

Abstract: Techniques are disclosed for preparing data for use in artificial intelligence (AI)-based cardiac arrhythmia detection. In accordance with the techniques of this disclosure, a computing system may obtain a cardiac electrogram (EGM) strip that represents a waveform of a cardiac rhythm of a same patient. Additionally, the computing system may preprocess the cardiac EGM strip. The computing system may then apply a deep learning model to the preprocessed cardiac EGM strip to generate arrhythmia data indicating whether the cardiac EGM strip represents one or more occurrences of one or more cardiac arrhythmias.