Abstract: The disclosure is concerned with privacy and integrity of personalized protected health information when transmitted to a cloud computing facility and subsequently distributed to a plurality of stakeholders. An electronic unit of a drug delivery device is configured to prepare payload data comprising data items according to an allocation scheme, and to encrypt, based on an encryption key, and transmit data including the payload data. The allocation scheme and the encryption key are defined for each of a plurality of data subscribers. Accordingly, personalized protected health information payload data is suitably protected with generator-to-subscriber or pass-through data security measures, and any intermediary node or data server in the communication network lacking a matching decryption key will not have access to unencrypted payload data.

Abstract: Methods and non-transitory machine-readable media associated with treatment plan identification are described. Treatment plan identification can include receiving first signaling configured to monitor user health data and receiving second signaling configured to monitor user behavior data. Treatment plan identification can include writing data that is based at least in part on a combination of the first signaling and the second signaling and identifying output data representative of a treatment plan for the user based at least in part on input data representative of the written data and additional user data. Output data representative of the treatment plan can be transmitted to a computing device accessible by the user, a computing device accessible by a provider, or both.

Abstract: A cloud-based application generates food product recommendations in support of medical nutritional therapy. The recommendations are calculated based on at least one patient-specific nutritional prescription and extended ingredient data that identifies food product ingredients or nutritional calculations that do not appear on packaging labels. The patient-specific nutritional prescription is calculated based on a patient profile and at least one nutritional prescription template. The recommendations may be used to perform a pantry makeover in which harmful food products are removed from household food storage and beneficial food products are added to household food storage. Recommendations may be calculated in real-time for food products that are identified during food shopping. Less harmful alternative food products are identified and suggested.

Abstract: A method for mitigating the spread of infectious diseases among dialysis patients is provided. The method comprises: receiving, by a prediction system and from a medical facility, individual treatment data indicating dialysis treatment information associated with a patient undergoing dialysis treatment; receiving, by the prediction system and from a blood testing laboratory, individual lab data indicating blood analysis information associated with the patient; determining, by the prediction system, disease analysis results for the patient based on inputting the individual treatment data and the individual lab data into a disease prediction machine learning (ML) model, wherein the disease analysis results indicate a likelihood of the patient being infected with a contagious disease; and providing, by the prediction system and to the medical facility, instructions indicating one or more responsive actions based on the disease analysis results.

Abstract: A user score of a test for assessing a risk of a user of having or developing a contagious illness may be obtained, for each user of a plurality of users entering in a group setting. A group score based on the user scores associated with the plurality of users in the group setting may be generated. The group score indicating a group risk of a presence or development of the contagious illness in the group setting may be communicated for display. Group scores associated with a plurality of group settings may be obtained and communicated for display. A message may be communicated to a mobile user device indicating a group setting as a current high risk group setting, being associated with a score that is outside a limit set by a threshold value and with a location in proximity to a current location of the mobile user device.

Abstract: The present disclosure provides systems and methods that leverage machine-learned models in conjunction with user-associated data and disease prevalence mapping to predict disease infections with improved user privacy. In one example, a computer-implemented method can include obtaining, by a user computing device associated with a user, a machine-learned prediction model configured to predict a probability that the user may be infected with a disease based at least in part on user-associated data associated with the user. The method can further include receiving, by the user computing device, the user-associated data associated with the user. The method can further include providing, by the user computing device, the user-associated data as input to the machine-learned prediction model, the machine-learned prediction model being implemented on the user computing device.

Abstract: This invention describes how users can capture digital artifacts from any medical device using their mobile device. Some examples of medical devices included, but are not limited to a medical ID card, Medical ID bracelet, Electronic Medical Records, blood pressure machines, blood glucose, scales, inhalers, INR, prescription bottles and trays, pulse oximeter, etc. Digital artifacts included, but are not limited to a medical ID, basic patient information, patient contact information, emergency contact information, primary care physician information, health insurance information including co-pay and deductibles, prescriptions, office visit summary, appointment cards, Electronic Medical Records (EMR), lab results, blood type, organ/donor status, vital signs, diagnostic data, immunization records, payments and transaction history, pictures, etc.

Abstract: A system and method for developing a treatment plan using multi-stage machine learning. A method includes determining a treatment plan for a patient based on at least one mental health disorder of a patient, wherein the treatment plan includes a plurality of digital therapeutics exercise tasks, wherein each digital therapeutics exercise task is selected from among a category of digital therapeutics exercise tasks corresponding to a type of mental health disorder of the at least one mental health disorder of the patient; and administering treatment to the patient by prescribing the treatment plan to the patient and causing data for administering the treatment plan to a user device of the patient.

Abstract: A wearable device can present virtual content to the wearer for many applications in a healthcare setting. The wearer may be a patient or a healthcare provider (HCP). Such applications can include, but are not limited to, access, display, and modification of patient medical records and sharing patient medical records among authorized HCPs.

Abstract: Systems and methods are provided for remote patient management and monitoring. The patient is monitored with a wireless sensor system connected to an application executing on a patient user computing device. The system continuously monitors physiological parameters, such as, but not limited to, blood oxygen saturation (SpO2), pulse rate, perfusion index, pleth variability index, and/or respiration rate from the photoplethysmograph. The system triggers alarms if the patient physiological data violates thresholds. Care providers review patient data and associated alarm(s) with graphical user interfaces.

Abstract: Methods, apparatuses, and systems for maintaining and controlling surgical tools are disclosed. For each surgical tool, a surgeon can give verbal commands which can result in feedback provided by a synthesized voice or the execution of an action as instructed by the verbal command. The tools are monitored during use to ensure the tools remain within their operating parameters. The system alerts the surgeon should the tools approach their operational limitations.

Abstract: Systems, methods and computer-readable media are provided for identifying patients having an elevated near-term risk of chronic kidney disease (CKD) progression, including predicting an individual's risk of progression to Stage 3 CKD within a future time interval, which may be up to 36 months. Based on the prediction, appropriate care providers may be notified so that the risk of CKD progression may be mitigated. In an embodiment, measurements of physiological variables are obtained, including serial measurements for uric acid levels from a longitudinal time series of serum or plasma samples spanning the previous two to five years. An annualized uric acid velocity of the patient is determined and used to generate a multivariable mathematical model for determining a likelihood of risk for developing Stage 3 CKD within 36 months.

Abstract: A method of controlling user equipment for a medical checkup and an apparatus for performing the method include controlling user equipment for a medical checkup the includes generating digital biomarker control data by a diagnosis server on the basis of prescription data, and transmitting the digital biomarker control data to user equipment by the diagnosis server, wherein the digital biomarker control data includes information for controlling a digital biomarker module of the user equipment.

Abstract: Embodiments of the invention provide decision support services, including an enhanced user interface. A reason for a clinical visit is determined and an initial workflow may be provided via the user interface during a clinical visit. The workflow may include a set of initial user interface elements that are determined based on a context associated with the clinical visit. The set of initial user interface elements may include a first initial interface element associated with a pre-identified clinical concept. During the clinical visit, a first suggested interface element can be provided. The first suggested interface element is generated during the workflow based on detecting a selection of the first initial interface element. The first suggested interface element can be associated with a first suggested clinical concept that is related to the pre-identified clinical concept.

Abstract: A mechanism is provided in a data processing system to implement a multi-sensor health monitoring platform. The mechanism applies a machine learning model to predict patient needs and patient activity trends based on physiological features and activity features of the patient. The mechanism applies the machine learning model to predict energy requirements for a plurality of medical sensors based on the predicted patient needs and patient activity trends. The mechanism schedules recharging of the plurality of medical sensors based on the predicted energy requirements and identifying one or more sensors to set to an activate state based on the predicted patient needs and patient activity trends. The mechanism collecting sensor data from the one or more sensors and applies the machine learning model to generate a point-of-care recommendation based on the collected sensor data.

Abstract: A system for improving cognitive ability includes a content providing module configured to provide a cognitive ability improving content; an input module configured to receive learning data of the user for the cognitive ability improving content; an analyzing module configured to calculate performance information of each of a plurality of cognitive areas based on the learning data; and a machine learning module configured to store a learning result by machine learning using a preset training data set and determine a characteristic of a cognitive ability improving content to be provided to a user by using the performance information of each of the plurality of cognitive areas and the learning result. According to the system for improving cognitive ability, it is possible to provide a content in the form of a comprehensive program including multi-area intervention important for dementia prevention and perform a customized dementia prevention function by reflecting individual characteristics.

Abstract: A trial operations service suite system and method in a clinical trial operations system with a patient portal providing patient-directed access to clinical trial operation services, a clinician portal providing clinician-directed access to the clinical trial operation service, and a coordinator portal providing coordinator-directed access to the clinical trial operation services, the coordinator portal also providing access to a trial design service wherein the trial design service is configured to allow a coordinator user to at least one of design, create, establish, and deploy a trial protocol and a participant interaction procedure, and a synchronization capability, synchronizing when online, information collected while a portal-supporting application is offline.

Abstract: A dental formula information input method and a dental formula information input device for automatically inputting dental formula information about teeth are disclosed. The dental formula information input method creates a library from dental formula information about teeth universally used for prosthetic work, and then automatically inputs the dental formula information about teeth through one click on the basis of the library, thereby minimizing work steps and enabling an increase in the convenience and usability of a user inputting cases relating to prosthetic work.

Abstract: An estimate of a functional capacity such as VO2Max is made by applying the vital signs of a monitored human to a trained encoding neural network producing a cardio profile vector. The vector is applied to a trained functional capacity (VO2Max) neural network to estimate the functional capacity. Once estimated, an action is taken.

Abstract: Various embodiments provide for decentralized crowd sourced generation of recommendation data objects. An example apparatus receives, originating from an external computing device, a recommendation data object request, the recommendation data object request comprising a user identifier and one or more user attributes. The example apparatus may further retrieve, based on a predictive recommendation model, one or more therapy identifiers associated with a therapy efficacy score exceeding a therapy efficacy score threshold for attributes of a first attributes set associated with a first cluster identifier, the first attributes set comprising one or more of the one or more user attributes.