Abstract: The disclosed embodiments include a computer-implemented method for communications centric care. A caregiver interface serves a patient interface in accordance with a disease management program to collaboratively lead the patient to recover from a disease. The method can include obtaining content items relating to a patient and labeling each content item as either a secure content item or an unsecure content item, and then comparing the labels with identifiers of the patient, the caregiver, and/or a schedule key events of the disease management program. The content items are selectively bifurcated for the patient and/or caregiver interfaces. As such, the interfaces can manage communications in accordance with the disease management program.

Abstract: A computer program product for gathering respondent input for determining a ranking of states each characterized by a set of selected levels each associated to an attribute. The interface mechanism provides for inputting selected attribute levels of a respondent state and for ranking of comparable alternative states determined in response to the inputted respondent state, in comparison with that respondent state. The alternative states are each displayed as the set of attributes with the associated set of alternative levels simultaneously and with an input field for inputting a preference indication of the shown alternative state compared with the respondent state. This allows the respondent input to be entered with very few input actions and little switching between screens. Only the selected attribute levels of the respondent state and the rankings and identifications of the determined alternative states need to be transmitted to the central computer.

Abstract: Methods and systems for providing treatment planning information for a neurology procedure, including neurosurgical procedures. A database containing historical data about historical procedures is accessed. Historical data relevant to a neurology procedure is determined, based on a determination of similarity to a set of data characterizing the neurology procedure. Historical instances of procedure parameters relevant to the neurology procedure are determined and displayed.

Abstract: A computer-implemented method for generating anatomical data associated with a musculoskeletal joint, the method comprising: receiving as input variation data representing change with time of a musculoskeletal joint of interest caused by a condition; receiving as input patient data representing the musculoskeletal joint of interest of a patient at a current time; and processing the variation data and the patient data to generate said anatomical data, wherein said anatomical data comprises data indicating the musculoskeletal joint of interest of the patient at a predetermined time different to the current time.

Abstract: A method for quantifying the balance of an individual recording, on a memory, at least one statokinesigram of the individual obtained from a platform comprising pressure and/or force sensors; extracting, by a processor and from the at least one statokinesigram of the individual recorded on the memory, values of at least one position trajectory parameter of the pressure center and values of at least one stability trajectory parameter of the pressure center; determining, by the processor, the value of a plurality of quantifiers, from the values of the trajectory parameters extracted; comparing, by the processor, said values of the plurality of quantifiers with the values of the same quantifiers obtained from reference statokinesigrams; and determining, by the processor, said value representative of the balance of the individual at the end of the comparison.

Abstract: A computer-implemented method for dynamically reallocating resources to users of a coaching service. The method can include initially allocating resources to users of the coaching service, receiving indications of activities of the users relative to their allocated resources, and comparing the activities relative to a reference value to produce an outcome including a likelihood that a target user will benefit from a target resource. Upon identifying the target user, a dynamic reallocation process deallocates the target resource from another user and reallocates the target resource to the target user.

Abstract: A system configured to receive health data pertaining to a user; select a user health profile from a plurality of user health profiles based on the collected health data, each of the plurality of user health profiles being associated with a health and wellness program and a set of interventions; receive user activity data and updated health data pertaining to, or during the user's participation in the associated health and wellness program from health devices; select a new set of interventions based on the user activity data; and select a new user health profile from the plurality of user health profiles based on at least one of the user activity data and the updated health data.

Abstract: Embodiments of the invention are directed to a system, method, or computer program product for a medical diagnostic platform. The system accesses data collected on one or more source server systems and selectively extracts user information according to the desired criteria of an operator or user. The system generates a secure, user database, wherein the user database comprises the selectively extracted user information, such as medical, financial, and demographic information, from multiple source server systems creating a centralized database of user information stored in a single location. The system further generates a medical diagnostic analysis of the user in comparison to similar users and displays recommended and extrapolated results for diagnoses, procedures, treatments, and costs for the user based on the history of the similar users.

Abstract: A system, including a memory storing instructions and a processor configured to execute the instructions is provided. The instructions executed by the processor cause the system to retrieve a diagnostic information for a patient, to retrieve a physician information for a physician in charge of the patient, and to determine an anticipated medication prescription for the patient based on the diagnostic information, the physician information, and a medication prescribing pattern stored in the memory. A method for using the system and a non-transitory, computer readable medium including the instructions are also provided.

Abstract: The present disclosure pertains to a system configured to generate computer simulations of patient loads for units of health care facilities. The system is configured to: obtain past patient census information for an individual unit of a health care facility, the past patient census information comprising a quantity of patient visits to the individual unit during past periods of time; determine intra-period variation and inter-period variation in the quantity of patient visits to the individual unit during the past periods of time; classify the individual unit based on the intra-period and inter-period variations; and generate a computer simulation of patient loads for the individual unit based on the classification. The computer-simulated patient loads comprise a quantity of patient visits to the individual unit during one or more future periods of time. The computer simulation is performed using a non-parametric simulation algorithm.

Abstract: Mechanisms are provided for training a hybrid machine learning (ML) computer model to simulate a biophysical system of a patient and predict patient classifications based on results of simulating the biophysical system. A mechanistic model is executed to generate a training dataset. A surrogate ML model is trained to replicate logic of the mechanistic computer model and generate patient feature outputs based on surrogate ML model input parameters. A transformation ML model is trained to transform patient feature outputs of the surrogate ML model into a distribution of patient features. A generative ML model is trained to encode samples from a uniform distribution of input patient data into mechanistic model parameter inputs that are coherent to the target distribution of patient features and are input to the surrogate ML model. Input patient data for a patient is processed through the ML models to predict a patient classification for the patient.

Abstract: Systems, methods and computer-readable media are provided for facilitating clinical decision support and managing patient population health by health-related entities including caregivers, health care administrators, insurance providers, and patients.

Abstract: Computerized systems and methods facilitate searches by identifying instances in which search input is an ambiguous query and resolving the ambiguous query. The search system identifies ambiguous queries by querying a common data store prior to querying a patient database. More particularly, when the search system receives search input entered into a search tool, the search system queries the common name data store before querying the patient database to determine if the search input matches a common name and is an ambiguous query. If so, the search system may provide a notification to the user to indicate the search input is an ambiguous query with a common name and prompt the user to enter additional search criteria. In some instances, the search system may prevent a search from being performed on the patient database if the search input matches a common name until additional search criteria is entered.

Abstract: A machine learning system for training a data model to predict data states in medical orders is described. The machine learning system is configured to train a data model to predict whether a medical order requires prior authorization (“PA”) for medical orders within a medical order data set so that related systems may process incoming medical orders with PA determinations predicted by the data model. The machine learning system includes a first data warehouse system. The first prescription processing system generates a data model of historical orders and payer responses, apply a predictive machine learning model to the data model to generate a trained predictor of whether a medical order requires PA, associated with order data, apply the trained predictor to a plurality of production orders to determine PA for each of the plurality of production orders, and process the plurality of production orders with each associated PA determination.

Abstract: A dossier change control management system periodically ingests data regarding a regulated product from multiple data stores. The dossier change control management system updates dossier data describing a dossier history for the regulated product using the received data. The dossier includes multiple documents in a standardized format and is updated based on a data mapping indicating correspondence between fields of the documents and portions of the received data. An out-of-expectation scenario for the dossier is identified based on regulatory requirements and an alert generated. A report with information about the out-of-expectation scenario is provided for display at a client device based on the alert.

Abstract: A mechanism is provided in a data processing system comprising at least one processor and at least one memory, the at least one memory comprising instructions that are executed by the at least one processor and configure the at least one processor to implement a medical record to illustrative medical image translation engine. The medical record to illustrative medical image translation engine receives a medical record batch from storage for a patient and generates one or more predicted prognosis records based on the medical record batch using a neural network. The medical record to illustrative medical image translation engine converts the one or more predicted prognosis records to illustrative medical images using a first agent. The medical record to illustrative medical image translation engine generates a presentation of disease progression using the illustrative medical images and outputs the presentation to a user.

Abstract: A risk evaluation system is provided with an imager and a controller. The imager takes images at different times of equipment having zones that do not overlap each other, and outputs the images that are taken. The controller detects a contact count of a number of times a living body contacts each of the zones in accordance with the images, decides evaluation information about a contact infection risk in each of the zones in accordance with the contact count, and outputs the evaluation information.

Abstract: A system and method for alerting a healthcare provider to ineffective prescribed medications is provided. A laboratory system receives test results with genetic markers for a patient, queries a database containing medications known to be ineffective in persons having particular genetic markers to determine whether any medications prescribed by, or likely to be prescribed by, a healthcare provider to the patient are known to be ineffective in persons having the same genetic markers as the patient, and transmits an alert containing such information to a healthcare provider system for the healthcare provider.

Abstract: Systems, methods and computer-readable media are provided for facilitating clinical decision support and managing patient population health by health-related entities including caregivers, health care administrators, insurance providers, and patients.

Abstract: Systems, methods and computer-readable media are provided for facilitating clinical decision support and managing patient population health by health-related entities including caregivers, health care administrators, insurance providers, and patients.