Abstract: Embodiments of the invention include a cloud-assisted rehabilitation system for assisting in the rehabilitation of musculoskeletal conditions, and a method for rehabilitating patients having musculoskeletal conditions. A rehabilitation portal can aggregate and de-identified musculoskeletal rehabilitation information that is gathered from various intelligent musculoskeletal rehabilitation apparatuses attached to a group of patients. The rehabilitation portal can facilitate crowd communication among the group of patients. A particular rehabilitation experience can be compared with other rehabilitation experiences and data from other patients. The rehabilitation portal can also facilitate crowd communication among a group of healthcare professionals so that the plurality of healthcare professionals can communicate with each other and compare information regarding different rehabilitation experiences based at least on the aggregated de-identified musculoskeletal rehabilitation information.

Abstract: A computer-implemented system assists resolution of service cases for medical imaging devices by retrieving device and case data, estimating likelihoods and timeframes for multiple resolution pathways, and presenting results in a user interface. Input may include images of device error messages captured by a camera; optical character recognition extracts text, and language detection and translation normalize messages for analysis. Models leverage historical repair data, technician profiles, and part replacement indicators to score pathways and forecast durations. A cost metric can combine likelihood and timeframe with service and scheduling costs to recommend actions and trigger service calls. The approach reduces downtime and improves dispatch and repair efficiency across customer and provider personnel.

Abstract: The present invention offers a novel, integrated, multi-source input, data-based personalized health, exercise and fitness system and method. The system offers personalized fitness plans based on a user's disparate input sources. The system can ingest both asynchronous and synchronous inputs to improve health fitness results. A screen with camera, preferably in a mirror design is a central component of the invention.

Abstract: A computer-implemented method is described for contextualizing medical events and detecting errors, for example, in claims data. The method may include receiving medical event data from one or more reporting entities, and converting the received data by normalizing and grouping by provider and by medical event. The converted data is presented to the subject of the medical event(s), via a user interface (UI). The UI includes one or more interactive graphical elements (e.g., virtual buttons) each configured to provide feedback on specific aspects of the converted data for the medical event. Based on input from the subject via the UI, it is determined whether the subject believes the received data is correct. If the data is indicated to be incorrect, further investigation may be triggered, and the payor and/or reporting entity may be alerted.

Abstract: A computer-implemented system and method enable real-time healthcare transaction processing based on ambient audio captured during physician-patient conversations. The system includes one or more microphones to receive spoken dialogue and a speech recognition engine to transcribe the audio into text. A natural language processing module analyzes the text to identify clinical intents corresponding to healthcare transactions. The identified intent is standardized into a structured query format and transmitted to an external system via a communications interface. In response, the system receives external data such as insurance coverage status, cost estimates, or authorization requirements. A user interface displays the external response in real time during the clinical encounter, allowing the physician or patient to make informed decisions. Additional modules may include context monitoring logic to suppress non-actionable utterances and a secure storage engine to log queries and responses.

Abstract: A method for determining a social health score for a region includes receiving first data for a geographical area. The first data includes values for multiple features corresponding to multiple domains (such as economic, education, and environmental). The method includes, for a first domain, selecting a first set of features (for example, an environmental domain may include a feature that describes the amount of the geographical area covered by impervious surfaces), and determining weights for the first set of features. The method includes receiving second data for the region and determining a first region domain score based on the second data and the first feature weights. The method includes determining a total score for the region based on the first region domain score that indicates a level of resource access for a population of the region.

Abstract: Provided herein are systems, methods, and apparatuses for providing a real-time global bio-surveillance and response solution. The systems and apparatuses may include one or more sentinel subsystems and one or more surge subsystems that each include a real-time, cloud-based, distributed, interconnected set of hardware, software, and/or firmware for comprehensive surveillance, complete detection, and immediate response various to biological, chemical, and/or bio-chemical anomalies, for example, a new or emerging pathogen or other health condition.

Abstract: A cloud-based, query management and education system enables provider organizations to query and educate clinicians on how to clarify clinical documentation, resulting in more accurate reimbursement, public reporting, research and policy decisions. Query authors create compliant queries from stored templates which may be supplemented by attaching and/or annotating selected documentation from the patient record. Clinician responses to such queries automatically generate addenda in the relevant patient record. All events around a query are tracked and reportable through a graphical performance scorecards and reporting dashboards.

Abstract: A clinical documentation improvement (CDI) smart scoring method may include predicting, via per-condition diagnosis machine learning (ML) models and based on clinical evidence received by a system, a probability that a medical condition is under-documented and, via per-condition documentation ML models and based on documentation received by the system, a probability that a medical condition is over-documented. The under- and over-documentation scores are combined in view of special indicators and queryability factors, which can also be evaluated using ML query prediction models, to generate an initial CDI score. This CDI score can be further adjusted, if necessary or desired, to account for factors such as length of stay, payer, patient location, CDI review timing, etc. The final CDI score can be used to prioritize patient cases for review by CDI specialists to quickly and efficiently identify meaningful CDI opportunities.

Abstract: A system and process for dynamically managing a procedure. The system includes a data collection device(s) that objectively monitor a subject and transmit such information to the system and real time position components that report on the availability of an individual(s) to perform the procedure. The system reviews the information, provides a subject diagnosis and recommends equipment. The system can also schedule and monitor the procedure. The individual(s) performing the procedure have the option of consulting with relevant experts and visually interacting with the experts.

Abstract: Point of care ultrasound examinations can be routed and processed in a computer network via the platforms, systems, and methods disclosed herein. The platforms, systems, and/or methods can use computing devices that are configured to provide a client application and at least one server processor for enabling use of an application. The examinations can be managed using an interface that allows an administrator user to assign user roles to other users, which can enable interactions within the network for processing and serving an ultrasound exam object. The ultrasound exam object can include patient data, images, and/or other relevant information.

Abstract: A computer-implemented method for determining risk scores using machine learning based on sensor data. The method includes receiving sensor data and demographic data for a user, determining a pattern of behavior based on the sensor data and demographic data, identifying a plurality of test groups based on other users that exhibit similar patterns of behavior to each other where sensor data from other users' electronic devices are received, identifying a test group corresponding to the user from among the plurality of test groups, determining a risk score using a trained risk analyzer machine learning model trained with historical sensor data, historical demographic data, and feedback data indicative of incidents, identifying risk mitigation strategies based on the risk score, refining the risk mitigation strategies using an iterative machine learning process as additional feedback data is collected, and retrieving risk mitigation communications from a database when the risk score exceeds a threshold.

Abstract: A wireless locating system and method include receiving first messages at a server. The first messages include bed location data entered manually on a user interface of a first patient bed. The first messages also include signal strength data from a plurality of wireless access points in communication with the first patient bed. A first signal strength profile for the first patient bed at a first location is built by the server. The first patient bed is removed from the first location and a second bed is moved into the first location. The second patient bed does not have manual location data entry capability. A second signal strength profile is built by the server for the second patient bed. The server compares the second signal strength profile with the first signal strength profile and determines that the second patient bed is at the first location if the second signal strength profile matches the first signal strength profile.

Abstract: Methods for communicating risk of skin conditions due to exposure to sunlight and environmental conditions to individuals. Methods utilize geolocation data and environmental data to provide guidance and enable consumers to make informed decisions regarding outdoor activities, healthcare, and skincare. A photopollution metric is a function of ultraviolet index (UVI) and the level of a pollutant such as particulate matter (PM) and enables communication of risk of exposome-induced skin conditions to an individual based on environmental exposure.

Abstract: A system may receive radiology data, outcome data for one or more exams, and elapsed time data for the one or more exams. The system may train a first machine learning algorithm to detect exams that are candidates for cherry-picking using the set of radiology data, outcome, and elapsed time data. The system may further determine, using the radiology data and the first machine learning algorithm, a likelihood that an exam was rejected due to cherry-picking.

Abstract: A system, method and wireless earpieces for populating an electronic medical record utilizing wireless earpieces. The sensor measurements are analyzed. The sensor measurements are associated with the electronic medical record of the user. The electronic medical record of the user is populated with the sensor measurements. Communications including the electronic medical record are communicated.

Abstract: A patient portal system may include a patient database module to interpret a patient profile value and a clinical database module to interpret a clinical study description. The patient database module may also interpret patient clinical data in response to the patient profile value and the clinical study description, and include at least a portion of the patient clinical data as longitudinal data of a patient corresponding to the patient profile value. The system may also include a patient interface module to implement a patient engagement interface and to interpret a patient medical event value in response to patient interactions with the patient engagement interface. The patient database may also adjust the longitudinal data in response to the patient medical event value.

Abstract: The present disclosure provides a data processing method and device, the method includes: acquiring exercise data of a user in a preset time period and a physical parameter preset by the user, wherein the exercise data comprises exercise data of a head, a hand and a leg of the user; and inputting the exercise data and the physical parameter into a pre-trained energy determination model for processing to obtain energy consumed by the user in the preset time period.

Abstract: Examples in the present disclosure relate to multi-dimensional reinforcement learning in a digital platform. The digital platform maintains and updates user data associated with tracked users. One or more machine learning models process the user data to generate recommendation data that includes automatically generated exploratory program elements for known activity programs of respective users of the digital platform. The exploratory program elements are validated by supervising users before implementation. The digital platform continuously updates the one or more machine learning models using dual reinforcement signals: one based on supervising user-validated recommendations and another based on activity program results. Further recommendation data is generated after updating the one or more machine learning models.

Abstract: A surgical computing system may provide first information about a surgical procedure to a recommendation model. The first information may include the identity of an observation point of a surgical device to be used during the surgical procedure. The surgical device may collect data descriptive of an object of the observation point. The surgical computing system may receive second information from the recommendation model. The second information may be indicative of a recommended schema for the observation point. The recommended schema may define a timing via which the surgical device is to collect data. The surgical computing device may send, to the surgical device, an instruction to collect, during the surgical procedure, data descriptive of an object of the observation point according to the timing defined by the recommended schema.