Abstract: A method of generating a treatment plan for treating a patient with radiotherapy, the method includes obtaining a plurality of sample plans, which are generated by use of a knowledge base comprising historical treatment plans and patient data. The method also includes performing a multi-criteria optimization based on the plurality of sample plans to construct a Pareto frontier, where the plurality of sample plans are evaluated with at least two objectives measuring qualities of the plurality of sample plans such that treatment plans on the constructed Pareto frontier are Pareto optimal with respect to the objectives. The method further includes identifying a treatment plan by use of the constructed Pareto frontier.

Abstract: A Statistical financial system to value patient visits to healthcare providers allows healthcare providers to optimize their financial outcomes when billing insurance payers for services rendered in the course of patient visits. Commercial healthcare information systems today lack the ability to value these services in advance. Given the complexity of valuing services based on many variables and resource limitations, a predictive valuation provides the user with the information for accurate and timely decision making Using the historical data, the system creates a predictive model of future claims by creating attribute patterns from the data. As new information comes into the system, these attribute patterns are compared to the real-time data in order to create a value for a service and an overall visit. Using the valuation, the system will now be able to prioritize all follow-up tasks. The overall result is a better financial performance for the healthcare provider.

Abstract: A method for monitoring a medical device (DM) available to a patient (P), the medical device (DM) including a communication terminal (T) implementing software functionalities (f1, f2, f3) for accompanying the patient (P) in a predetermined therapeutic treatment, the method including: —a step (S1) of receiving the current data (DC) on execution of the software functionalities (f1, f2, f3) coming from the medical device (DM), —a step (S2) of testing the current data (DC) by comparison with reference data (DR) according to at least one predetermined vigilance rule (R) associated with a risk for the patient, and —a step (S3) of sending a vigilance message (M1) when such a risk is identified.

Abstract: Systems and methods of recording patient's medical documents and training programs for improving medical document recordation. The system includes a computer readable medium capable of storing medical data obtained from patients, including disease codes, a computer with software capable of evaluating the data stored on the computer readable medium for completeness, and a notification system capable of presenting to the user of the system a warning if any of the data is found to be incomplete or incorrect. The training includes evaluating the healthcare provider's current medical documentation process, training the healthcare provider in methods of recording medical documents, providing a system for recording medical documents, and training the healthcare provider in use of the system.

Abstract: Systems and methods for data unfolding are disclosed. For example, it may be desirable or necessary to increase a data set, such as for increasing accuracy of one or more predictive models. Data set proliferation without introducing unnecessary bias may be important for increasing such accuracy. Described herein are system and methods that allow for data set proliferation by generating records based on whether an event occurred with respect to an entity during multiple time intervals. A record may be generated for each time interval and the associated data may be unfolded and disassociated, at least partly, from other records related to the entity. Those records may then be used for data analytics and/or predictive model generation, for example.

Abstract: Methods, systems, and computer-readable media are provided for analyzing amounts of time spent by clinicians caring for patients. Clinician locations, patient locations, patient data, and clinician electronic health record activity may be used to facilitate generation of one or more predictive models. Such predictive models will provide, among other things, a decision support tool for scheduling patient-clinician appointments to minimize, at least partially, patient wait times.

Abstract: A system for selecting a health care provider and then monitoring and reporting the selected provider's performance. A processor is programmed to retrieve from the internet and store in a database historical performance data on providers and healthcare data relating to the providers' historical performance. The processor determines which provider should be selected to perform a task, by assessing the providers' historical performances against each other; selecting a provider to perform a task, monitoring post-selection healthcare data relating to the provider's performance of the task, and generating a reporting metric comprising a display of a trend in the selected provider's historical performance and/or the provider's current performance of the task.

Abstract: A system is used to control operation of a user device. An association between a medical condition and one or more decision trees is maintained. Each decision tree includes nodes organised in a tree structure originating at a root node and terminating at leaf nodes via branch nodes. The nodes are linked to each other via outputs and each output causes the system to differently control operation of the user device. Responsive to receiving medical information associated with the patient, using the association, a decision tree is identified. For the root node of the identified decision tree: a first node is selected, responsive to receiving data indicative of a first output regarding the root node; the user device is caused to retrieve medical information from one or more data sources based on the first node; and the retrieved medical information is caused to be displayed on the user device.

Abstract: Systems and methods to automatically generate classifiers are provided. A labeled dataset is initially received. The dataset may be for a positive class, or may be a negative for a class, or a false positive class. N features that are predictive for the class (or false positive or the negative class) are identified. These features are combined within a classifier dictionary. Medical records received may be processed in order to be machine readable. Features within the medical records are identified and are compared against the dictionary of classifiers. Matches indicate classes within the medical record. The classifier dictionary may be periodically updated in response to insufficient classification accuracy, or when new data becomes available.

Abstract: A model-assisted system and method for predicting health care services. In one implementation, a model-assisted system may comprise a least one processor programmed to access a database storing a medical record associated with a patient and analyze the medical record to identify a characteristic of the patient. The processor may determine a patient risk level indicating a likelihood that the patient will require a health care service within a predetermined time period; compare the patient risk level to a predetermined risk threshold; and generate a report indicating a recommended intervention for the patient. The processor may further determine a calibration factor indicating a difference between an average patient risk level and an average actual healthcare service usage for a first group of patients; and determine, based on the calibration factor, a bias relative to a second group of patients.

Abstract: Systems and methods are disclosed for receiving one or more digital images associated with a tissue specimen, a related case, a patient, and/or a plurality of clinical information, determining one or more of a prediction, a recommendation, and/or a plurality of data for the one or more digital images using a machine learning system, the machine learning system having been trained using a plurality of training images, to predict a biomarker and a plurality of genomic panel elements, and determining, based on the prediction, the recommendation, and/or the plurality of data, whether to log an output and at least one visualization region as part of a case history within a clinical reporting system.

Abstract: A medical device data management system comprising a server for updating data relating to medical devices, comprising a first database comprising a first plurality of data objects, wherein the first database is in communication with an interface via an interface application. The system comprises a second database comprising a second plurality of data objects containing an analogue of the data objects from the first plurality, wherein the second database is in communication with a plurality of medical devices via a medical device application. The system also comprises a synchronization application in communication with the first and second databases, and the synchronization application is configured to receive a notification when a data object from the first plurality changes in value, identify within the second plurality target analogues of the data object from the first plurality, and replace the target analogues with changed values of the data object from the first plurality.

Abstract: A system and method to determine and reconcile medication provided to a patient is disclosed. The system and method collect a medication image file (MIF) of a patient medication collection (PMC) using a mobile user device (MUD) and pill source imager (PSI). The MUD transmits the MIF to a host computer system (HSC) via a computer communication network (CCN). The HSC isolates individual MIF medication image elements (MIE) and compares each MIE against a pill image database (PID) to generate a potential pill match (PPM) list. The PPM is filtered and prioritized to produce a prioritized medication list (PML) using data from a pill correlation database (PCD), patient history database (PHD), and medical reading database (MRD). The PML describes probable PPM associations with specific known medications. A HCS graphical user interface (GUI) permits validation of each MIE/PML pair to produce a patient reconciled validated medication list (VML).

Abstract: A dental implant management system includes one or more processors operationally coupled to one or more computer storage mediums where the one or more processors causes the one or more processors to perform the operations of presenting a user interface having a plurality of tasks for completion, presenting a plurality of guided checklists for the dental implant process, inputting values for one or more of blood pressure, heart rate, blood oximetry, medical conditions, or allergies, and using artificial intelligence to modify the checklist based on previous data entered. In one embodiment, a listing of tasks is color coded for a status regarding each of the plurality of tasks. Other embodiments are disclosed.

Abstract: A mobile application is used for monitoring and management of users or patients with various health or disease conditions. Software system provides a platform with which the medical histories, the recent conditions and real-time measurement data for the patient can be organized and shared among various people who are involved in the caring of the patient. In addition to data sharing in a secured, private networking environment, the platform integrates the essential functions for people in the various caregivers' groups to communicate with each other in real-time so as to collaborate on the caring of the patient.

Abstract: A system and method for obtaining prior authorization and fulfilling a prescription is described. The method includes receiving, by a computing device, prescription information for a patient from a prescriber; identifying, by the computing device, an electronic health record associated with the patient; collecting, by the computing device, medical information for the patient related to the prescription from the electronic health record; submitting, by the computing device, a claim for the prescription with a payor associated with the patient; and completing, by the computing device, a prior authorization request for the prescription.

Abstract: Inference of appropriate anatomical region from inconsistent descriptions in order to provide fast and accurate prefetching is provided. In various embodiments, an anatomical region of a first medical imaging study is determined. A first plurality of keywords is determined corresponding to the anatomical region of the first medical imaging study. A plurality of studies is accessed having a patient in common with the first medical imaging study. A second plurality of keywords is extracted from the plurality of studies. Those of the plurality of studies having extracted keywords in common with the first plurality of keywords are selected. The selected studies are pre-fetched for display to a user.

Abstract: A conversational and embodied Virtual Assistant (VA) with Decision Support (DS) capabilities that can simulate and improve upon information gathering sessions between clinicians, researchers, and patients. The system incorporates a conversational and embodied VA and a DS and deploys natural interaction enabled by natural language processing, automatic speech recognition, and an animation framework capable of rendering character animation performances through generated verbal and nonverbal behaviors, all supplemented by on-screen prompts.

Abstract: The present invention provides a ready-to-use Cognitive Chart (CC) for follow-up of age-related cognitive decline. Similar to “growth curves”, this innovative model factors in age and education to determine whether elderly patients show abnormal performance on serial MMSE and longitudinal performance tracking and favors prompt initiation of investigation and treatment. A method for generation of said charts, and a use thereof is also provided.

Abstract: Systems and methods for demand and supply forecasting for clinical trials are disclosed. An embodiment of a computer-implemented method may include receiving, by a server from a user, one or more electronic files that contain parameters of a clinical trial, the parameters comprising a quantity of patients, a plurality of sites, and one or more confidence values, calculating, by the server, according to the quantity of patients, a respective demand profile for each of the plurality of sites, calculating, by the server, according to the one or more confidence values, a buffer quantity for each of the plurality of sites, calculating, by the server, a supply plan for the clinical trial according to the demand profiles and the buffer quantities, and transmitting, by the server, the supply plan to the user.