Abstract: Systems and methods are provided for adjusting a basal/bolus ratio in a standing insulin regimen for a subject that comprises daily amounts of basal and bolus insulin medicaments that define an initial basal/bolus ratio. A data set comprising glucose measurements of the subject with a respective timestamp for each such measurement over a time course is obtained. One or more fasting events are identified in the time course. A temporal glucose gradient is computed for each fasting event using the glucose measurements in the data set within the fasting event time period. Fasting event glucose gradients are used to determine whether to recommend adjustment to the basal/bolus ratio for the subject without change to the daily total insulin medicament. The recommended adjustment to the basal/bolus ratio is communicated when the determination is made to make the recommended adjustment to the basal/bolus ratio for the subject.

Abstract: The present disclosure provides for medical device administration and interaction by identifying a medical event affecting a first individual, a medical device associated with treating the medical event, and an initial attentiveness level of an administering individual; outputting a tutorial for how to use the medical device to treat the medical event with a first control level, wherein the first control level based on the initial attentiveness level of the administering individual; and in response to receiving a triggering event while outputting the tutorial: determining a current attentiveness level for the administering individual; and in response to the current attentiveness level indicating a change from the initial attentiveness level, adjusting the tutorial based on a second control level, different than the first control level, based on the change from the initial attentiveness level.

Abstract: A system for dietary communications using intelligent systems regarding endocrinal measurements includes a computing device designed and configured to obtain a first endocrinal measurement relating to a user; compare the first endocrinal measurement to an endocrinal system effect; generate a body dysfunction label for the first endocrinal measurement as a function of the endocrinal system effect; identify a dietary communication as a function of the body dysfunction label, the first endocrinal measurement, and a first machine learning process, the first machine learning process trained using a first training set relating endocrinal measurements and body dysfunction labels to dietary communications; and present the dietary communication.

Abstract: Graphical user interfaces for use with extracorporeal blood treatment systems may include a plurality of displayable settings cards. The plurality of settings cards may be grouped or arranged into a card set and a plurality of card subsets. Each of the card set and the plurality of card subsets may be displayable as a stack of settings cards with at least one settings card presented at the forefront of the stack to a user. Further, each settings card of the plurality of settings cards may also be displayed by itself.

Abstract: Systems and methods for selectively distributing programs to remote devices are described. In some implementations, one or more computers access candidate profile for a candidate to participate in interactive programs involving collection of data from participants using remote devices. The one or more computers also identify program profiles for multiple programs in which the candidate is eligible to enroll as a participant. Scores are determined for each of the programs with respect to the candidate, and one or more of the programs are selected for the candidate based on the scores. Selection results are provided over the communication network to a client device, the selection results being provided for presentation by the client device to indicate the selected one or more programs on an interface of the client device.

Abstract: Embodiments of the present systems and methods may provide techniques to predict the success or failure of a drug used for disease treatment. For example, a method of determining drug efficacy may include, for a plurality of patients, generating a directed acyclic graph from health related information of each patient comprising nodes representing a medical event of the patient, at least one first edge connecting the first node to an additional node, each additional edge connecting nodes representing two consecutive medical events, the edge having a weight based on a time difference between the two consecutive medical events, capturing a plurality of features from each directed acyclic graph, generating a binary graph classification model on captured features of each directed acyclic graph, determining a probability that a drug or treatment will be effective using the binary graph classification model, and determining a drug to be prescribed to a patient based on the determined probability.

Abstract: A medical scan diagnosing system is operable to receive a medical scan. Diagnosis data of the medical scan is generated by performing a medical scan inference function on the medical scan. The first medical scan is transmitted to a first client device associated with a user of the medical scan diagnosing system in response to the diagnosis data indicating that the medical scan corresponds to a non-normal diagnosis. The medical scan is displayed to the user via an interactive interface displayed by a display device corresponding to the first client device. Review data is received from the first client device, where the review data is generated by the first client device in response to a prompt via the interactive interface. Updated diagnosis data is generated based on the review data. The updated diagnosis data is transmitted to a second client device associated with a requesting entity.

Abstract: Cognitive medical treatment recommendation mechanisms are provided. The mechanisms ingest a corpus of medical treatment content that comprises drug-to-drug interaction information. The mechanisms generate a set of drug interaction insight data structures and an initial set of candidate treatments for a medical condition of a patient based on an analysis of an electronic medical record associated with the patient. The mechanisms rank candidate treatments in the initial set of candidate treatments based on the set of drug interaction insight data structures to generate a final set of candidate treatments, where the ranking reduces rankings of candidate treatments in which drug interactions are identified in the set of drug interaction insight data structures. The mechanisms output a treatment recommendation based on the final set of candidate treatments.

Abstract: A server computing device executing an electronic health records (EHR) receives an indication from a client computing device that approval from a pharmacy benefits manager (PBM) with respect to prescribing a medication and/or treatment to a patient is requested. The EHR causes the server computing device to transmit an approval request to a computing system of the PBM, and monitors incoming messages for an approval message from the PBM. When the approval message is received, the ERR constructs a prescription for the medication and/or treatment for the patient and causes the prescription to be transmitted to a pharmacy.

Abstract: Embodiments of the present disclosure disclose a distributed ledger technology (e.g., blockchain)-based system that provides tools and mechanisms to place users in control of their data. In embodiments, the system may include a platform device configured to initiate a connection with a lab test service provider whose systems (e.g., computer systems) may store data pertaining to the user. In embodiments, the platform device is configured to secure the data stored at the lab test service provider by facilitating deployment of that data into a distributed ledger. Once the data is secured in the distributed ledger, the platform device may be configured to provide controlled distribution or sharing of the secured data with other users or other third-party systems.

Abstract: Techniques for solving a radiotherapy treatment plan optimization problem are provided. The techniques include receiving a first radiotherapy treatment plan optimization problem having a first set of parameters; processing the first set of parameters to estimate a second set of parameters of a second radiotherapy treatment plan optimization problem; generating a solution to the second radiotherapy treatment plan optimization problem based on the estimated second set of parameters; and generating a radiotherapy treatment plan based on the solution to the second radiotherapy treatment plan optimization problem.

Abstract: Methods and Systems implement patient management. In some cases, a patient management system 200 may include one or more respiratory pressure therapy devices to deliver respiratory pressure therapy to patients, and generate therapy data relating to a therapy session for a patient. The patient management system may include a data server communicating with the therapy device(s). The data server may compute, from therapy data, therapy summary data for the session, the summary data may include one or more statistics summarising therapy data. The patient management system may include a therapy management server communicating with the data server. The therapy management server may apply one or more rules to the summary data, update or generate one or more workflow groups of patients, each workflow group corresponding to a rule, depending on results of the respective rule applications; and/or serve a graphical layout representing one or more workflow groups.

Abstract: A system to allocate resources via information technology infrastructure is described. A server includes processors to provide to a plurality of devices, an electronic benefits account transaction application programming interface (“API”) configured to receive transaction requests from a plurality of heterogeneous electronic funding sources. The server can receive a request to initiate a single transaction to fund an electronics benefit account. The server can transmit data in an alert format indicating a denial of the single request responsive to a comparison of a value to one or more threshold limits.

Abstract: A method and system for automated medical records processing with telemedicine is presented. The method and system includes plural electronic medical templates specifically designed such that they reduce the complexity and risk associated with collecting virtual patient encounter information, creating a medical diagnosis, tracking the patient through the medical processes during a telemedicine session and generate the appropriate number and type medical codes for a specific type of medical practice when processed. The medical codes and other types of processed virtual patient encounter information are displayed in real-time on electronic medical records and invoices immediately after a virtual patient encounter from a telemedicine visit.

Abstract: Methods, systems, and computer-readable media are provided for facilitating record matching and entity resolution and for enabling improvements in record linkage. A power-spectrum-based temporal pattern-specific weight may be incorporated into record linkage methods to enhance the record linkage accuracy and statistical performance. For example, in embodiments, a value-specific weight may be calculated from a population-based frequency of field-specific values and provides an opportunity to capture and measure the relative importance of specific values found in a field. A timeseries-derived Bayesian power spectrum weight may be calculated from the population-based frequency of temporal pattern-specific values in terms of intensities at various frequencies of the power spectrum computed from the timeseries, and further provides an opportunity to capture and measure the relative importance of specific sequences of care episodes.

Abstract: A system and method for generating an ocular dysfunction nourishment program comprises a computing device configured to receive at least an ocular attribute datum as a function of a user visual system, generate at least an ocular profile as a function of the at least an ocular attribute datum, wherein generating comprises receiving an ocular utopia as a function of an ocular guideline, and generating the at least an ocular profile as a function of the at least an ocular attribute datum and the ocular utopia using an ocular machine-learning model, identify at least an edible as a function of the at least an ocular profile, and develop a nourishment program of a plurality of nourishment programs as a function of the edible and a profile outcome using a nourishment machine-learning model.

Abstract: A system is provided to provide triage recommendations for animals. The system accesses a syndrome mapping of syndromes to complaints, each syndrome having a triage category. The system accesses a complaint mapping of complaints to symptoms. Each symptom for a complaint has a weight. The system receives indications of a current complaint and current symptoms of an animal. Each current symptom has a score. The system identifies the triage category based on a syndrome to which the current complaint and the current symptoms apply, factoring in the weights and the scores. The system provides a recommendation for the animal based on the identified triage category.

Abstract: This disclosure relates generally to method and system for graph convolution based gene prioritization on heterogeneous networks. The method includes obtaining a set of entities for human rare diseases from one or more sources containing rare diseases, genes, phenotypes for rare diseases and biological pathways and constructing an initial heterogeneous network using each of an entity from the set of entities. the initial heterogeneous network applying Graph Convolution-based Association Scoring (GCAS) to the initial heterogeneous network to derive inferred associations and creating a Heterogeneous Association Network for Rare Diseases (HANRD) by adding the inferred associations to the initial heterogeneous network and generating a prioritized set of genes for an input query being received in the HANRD.

Abstract: Methods or systems (7000) are implemented for treatment with or monitoring use of respiratory pressure therapy device(s). The device may be for a respiratory disorder. A processor, such as a processor of a server communicating with the therapy device, may analyse data relating to respiratory therapy delivered by the device. The processor may generate data in the processor representing a prediction, such as compliance prediction(s), about progress of therapy based on the analysis. The processor may select an action to improve therapy based on data representing the prediction. The processor may take or prompt selected action to improve the therapy. In some cases, a processor may analyse usage data concerning a period of days with a therapy device and generate compliance prediction indicators based on the analysis. The indicators indicate whether compliance will be likely. The processor may recommend engagement action to improve compliance based on evaluation of the indicators.

Abstract: A system 100 for automatically generating a field of a radiology report includes a set of one or more models. A method for automatically generating a field of a radiology report includes: receiving a radiologist identifier (radiologist ID); receiving a set of finding inputs; determining a context of each of the set of finding inputs; determining text associated with a portion or all of the radiology report based on the context and the radiologist style; and inserting the text into the report.