Abstract: A method is disclosed for generating treatment plans for optimizing patient outcome and monetary value amount generated. The method includes receiving a set of treatment plans that, when applied to patients, cause outcomes to be achieved by the patients, receiving a set of monetary value amounts associated with the set of treatment plans, receiving a set of constraints, where the set of constraints comprises rules pertaining to billing codes associated with the set of treatment plans. The method includes generating, by the artificial intelligence engine, optimal treatment plans for a patient, where the generating is based on the set of treatment plans, the set of monetary value amounts, and the set of constraints. Each of the optimal treatment plans complies with the set of constraints and represents a patient outcome and an associated monetary value amount generated. The method includes transmitting the optimal treatment plans to a computing device.

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 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 learning apparatus, a walking training apparatus, a method, a system, a program, and a trained model for performing walking training at appropriate setting parameters are provided. A learning apparatus according to an embodiment includes: a data acquisition unit configured to acquire rehabilitation data from a walking training apparatus including an actuator configured to assist a walking motion of a trainee and a control unit configured to control the actuator in accordance with a setting parameter; and a data generation unit configured to generate an index indicating a degree of recovery of the trainee and the setting parameter as learning data; and a learning unit configured to generate a learning model that receives the index and outputs a recommended value of the setting parameter by performing machine learning using the learning data.

Abstract: Methods, apparatuses, systems, computing devices, and/or the like are provided. An example method may include retrieving a plurality of natural language data objects from a database; determining, based at least in part on the plurality of natural language data objects and by utilizing an entity extraction machine learning model, a plurality of entity identifiers for the plurality of natural language data objects; determining, based at least in part on the plurality of entity identifiers and by utilizing the entity extraction machine learning model, one or more entity relationship identifiers for the plurality of natural language data objects; generating, based at least in part on the plurality of entity identifiers and the one or more entity relationship identifiers, a graph-based data object for the plurality of natural language data objects; and performing one or more prediction based actions based at least in part on the graph-based data object.

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: 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: Incorporation of deuterium into the lipids, proteins, and/or genetic material in cells, tissues, organs, or organisms, including animals, such as humans, and plants, by administration of heavy water, allows for the spectral determination of levels of lipids, proteins, and/or genetic material using Raman spectroscopy, such as stimulated Raman spectroscopy. Following administration of a drug, changes in the relative amounts of lipid, protein, and/or genetic materials can be determined, and the efficacy, or lack thereof, of the administered drug can be determined.

Abstract: Medical monitoring systems and methods are disclosed. A medical monitoring system can receive physiological parameter data and first physiological parameter alarm data from a plurality of patients. The first physiological parameter alarm data can be indicative of alarm conditions experienced by the plurality of patients. The alarm conditions can have been detected based upon first alarm criteria. The system can also generate second physiological parameter alarm data using a processor. The second physiological parameter alarm data can be indicative of simulated alarm conditions, which can be detected based upon a second alarm criteria. The system can compare the first and second physiological parameter alarm data using a processor.

Abstract: Machine learning based methods for planning, execution, and reporting of clinical trials, incorporating a patient burden index are disclosed. In one aspect, there is a method for determining a patient burden index. The method includes parsing a protocol for a clinical trial. The method further includes providing factor data for each of a plurality of patients. The method further includes calculating a patient burden index for each of the plurality of patients based on the parsed protocol and the provided factor data for each of the plurality of patients.

Abstract: A system and method for analyzing risk and providing risk mitigation instructions. The system receives analyzes sensor data and other data corresponding to a user to determine a test group. The system uses the test group to determine a risk score, and, subsequently, a risk mitigation strategy. Machine learning techniques are implemented to refine how the test group, risk score, and mitigation are each selected.

Abstract: Methods and systems disclosed to provide drug pricing information for display on a graphical user interface (GUI). The methods and systems may receive an electronic request that includes a first set of information that identifies a user, identifies a plurality of different pharmacy locations, and a prescription drug and omits a second set of information corresponding to a prescription for the prescription drug. The first set of information is transmitted to a database management module to access drug pricing information for the prescription drug for each of the pharmacy locations. The module compares the drug pricing information for each of the pharmacy locations, determines a potential savings based on comparing the prescription drug price between each of the pharmacy locations, and identifies the pharmacy location having the lowest price for the prescription drug and the potential savings for display via the GUI executing on the electronic device.

Abstract: An apparatus and computerized method of classifying a patient that has been previously diagnosed to have autosomal dominant polycystic kidney disease (ADPKD) includes providing a computing device having an input/output interface, one or more processors and a memory; receiving a total kidney volume (TKV), a patient height, and a patient age for the patient via the input/output interface; determining a height adjusted TKV (HtTKV) based on the total kidney volume and the patient height using the one or more processors; determining an ADPKD classification for the patient based on the height adjusted TKV and the patient age using the one or more processors; and providing the ADPKD classification for the patient via the input/output interface.

Abstract: A distributed system can include a server outside of a clinical environment and a connectivity adapter and a plurality of infusion pumps within the clinical environment. The connectivity adapter can receive from the server a location of an update, such as a drug library update or an operational software update, to be delivered to the infusion pumps. The location can be received over a first messaging communication channel of a network, and the update data can be received over a second, data communication channel of the network. The update data can be stored at the connectivity adapter such that it can be sent to the infusion pumps.

Abstract: Provided is a process, including: obtaining test data that quantifies a patient's cardiovascular status, the test data specifying patient attributes in a plurality of cardiovascular dimensions of the patient; determining a plurality of normalized differences between the test data and target criteria in each of the cardiovascular dimensions; determining predicted-effect vectors of each of a plurality of different classes of pharmaceuticals; determining an aggregate score for each respective class of pharmaceuticals among the different classes of pharmaceuticals based on values of the corresponding predicted-effect vectors; ranking the different classes of pharmaceuticals based on the aggregate scores; and outputting a recommended sequence of pharmaceuticals to administer.

Abstract: An augmented reality (AR) content generation method includes: acquiring, with a camera of an AR device, one or more images of a component of a medical imaging or medical therapy device; receiving, from a microphone of the AR device, a triggering audio segment; generating one or more query data structures from both the one or more images and the triggering audio segment; retrieving AR instructional content related to the medical imaging or medical therapy device matching the generated one or more query data structures from a database; and outputting the AR instructional content one or more of (i) displayed superimposed on video displayed by the AR device and/or (ii) displayed on a head mounted display of the AR device and/or (iii) as audio content via a loudspeaker of the AR device.

Abstract: Detection of anomalous computing environment behavior using glucose is described. An anomaly detection system receives glucose measurements and event records during a first time period. Missing events that are missing from the event records during the first time period are identified by processing the glucose measurements using an event engine simulator. An anomaly detection model is generated based on the missing events during the first time period. Subsequently, the anomaly detection system receives additional glucose measurements and additional event records during a second time period. Missing events that are missing from the additional event records during the second time period are identified by processing the additional glucose measurements using the event engine simulator. Anomalous behavior is detected if the identified missing events that are missing from the event records during the second time period are outside a predicted range of missing events of the anomaly detection model.

Abstract: A walking training apparatus is a motion support system that includes a walking assistance apparatus as an assistance apparatus, a selected assistance level setting unit, a load data acquisition unit, an angle sensor as a displacement sensor, and an overall control unit as a control unit. The assistance apparatus assists a motion of a joint performed by a user. The assistance level setting unit sets an assistance level that is a level of a force exerted by the assistance apparatus. The load data acquisition unit acquires load data related to a load of the assistance apparatus. The displacement sensor detects a displacement of the joint. The control unit determines a recommended assistance level, which is an assistance level to be recommended, based on the assistance level, the load data, and an output of the displacement sensor, and outputs information about the determined recommended assistance level.

Abstract: A method including receiving an input data set for an expectant mother during a time window, the input data set including fetal heart rate data; completing the input data set with a missing data sample to provide a completed data set; removing a segment from the completed data set based on at least one criterion to provide a corrected data set; calculating a baseline fetal heart rate based at least on the corrected data set; detecting an event occurring during the time window based at least on at least one of the corrected data set or the baseline fetal heart rate; classifying the event as either an acceleration, a deceleration, or a baseline change based on at least one of the corrected data set or the baseline fetal heart rate; and generating an output indicative of at least the event to enable an action with respect to the expectant mother.

Abstract: The present disclosure provides systems and methods for automatically generating telemedicine platforms for providers. A marketplace of healthcare services and associated pricing and other terms is made available to employers, individuals, and/or health insurance companies. Employers and/or health insurance companies can select a subset of options from the marketplace to create a customizable sub-marketplace of healthcare services to offer to their employees or insureds. Providers may modify their offerings in the marketplace to fit within guidelines established by the employers or health insurance companies to be automatically included in the sub-marketplace of healthcare services.