Abstract: Machine-learning techniques are used to train a classifier to predict auditory and language skills improvement in a patient who is a candidate for cochlear implantation (CI). One or more images of portions of the patient's brain are obtained, and quantitative data is extracted that represents the composition of one or more brain areas related to auditory and/or cognitive processing. For training of the classifier, data is obtained for previous CI patients whose improvement in language skills has been measured. Once trained, the classifier can be used to predict a likely degree of improvement in a prospective CI patient's auditory and language skills.

Abstract: Systems and methods for assessing a cardiac arrhythmia risk of a patient, such as a risk for developing atrial fibrillation, are disclosed. An exemplary medical-device system includes an arrhythmia predictor circuit configured to receive physiologic information of a patient, and in an absence of atrial tachyarrhythmia in the patient, determine a risk of the patient developing future atrial tachyarrhythmia using the physiologic information. In accordance with the arrhythmia risk indication, the system can generate an alert, or initiate more aggressive monitoring of a patient identified as having a high atrial tachyarrhythmia risk.

Abstract: A system and method for automatic coding of medical claims, so as to minimize or eliminate possible human error and oversight that is common with prior art solutions.

Abstract: A method (100) for training a scoring system (600) comprising the steps of: (i) providing (110) a scoring system comprising a scoring module (606); (ii) receiving (120) a training dataset comprising a plurality of patient data and treatment outcomes; (iii) analyzing (130), using a clinical decision support algorithm, the training dataset to generate a plurality of clinical decision support recommendations; (iv) clustering (140), using the scoring module, the plurality of clinical decision support recommendations into a plurality of clusters; and (v) identifying (160), using the scoring module, one or more features of at least one of the plurality of clusters, and generating, based on the identified one or more features, one or more inclusion criteria for the at least one of the plurality of clusters.

Abstract: According to an aspect of the present disclosure, a healthcare system receives a request to initiate a chat in relation to a patient, identifies healthcare providers having responsibility for the patient, and provides a chat session with the identified healthcare providers as participants. Upon receiving a command (requesting information on the patient) during the chat session, the healthcare system retrieves an electronic medical record (EMR) of the patient and sends the EMR to the participants of the chat session. In one embodiment, the command does not specify the identifier of the patient in the chat session. In another embodiment, when an external EMR system maintains EMRs of the patient, the healthcare system retrieves the EMR of the patient from the EMR system without requiring the participant to manually authenticate after specifying the command. Accordingly, the healthcare system is configured to facilitate collaboration among healthcare providers.

Abstract: Medical devices and related systems and methods are provided. A method of providing a notification pertaining to a physiological condition using a translation model involves identifying an error metric associated with an input variable associated with the translation model, determining a reference output of the translation model by providing reference values for the input variable to the translation model, generating modulated values for the input variable based on the reference values using the error metric, determining a simulated output of the translation model by providing the modulated values for the input variable to the translation model, and updating the translation model to reduce a weighting associated with the input variable when a difference between the simulated output and the reference output is greater than a threshold.

Abstract: Methods and systems including an N-butyl cyanoacrylate (“n-BCA”) liquid embolic agent and achieving, by the n-BCA liquid embolization agent, a reduction in total cost of preoperative embolization procedures for a plurality of patients versus an ethylene vinyl alcohol copolymer (“EVOH”) liquid embolic agent. Methods and systems for reducing supply costs of preoperative embolization by at least approximately 18% are described.

Abstract: Methods and systems are provided for automatically determining a phase shift and noise insensitive similarity metric for electrocardiogram (ECG) beats in a Holter monitor recording. In one embodiment, a deep neural network may be trained to map an ECG beat to a phase shift insensitive and noise insensitive feature space embedding using a training data triad, wherein the training data triad may be produced by a method comprising: selecting a first beat and a second beat recorded via one or more Holter monitors, determining a dynamic time warping (DTW) distance between the first beat and the second beat, setting a similarity label for the first beat and the second beat based on the DTW distance, and storing the first beat, the second beat, and the similarity label, in a location of non-transitory memory as an ECG training data triad.

Abstract: The present invention is directed to a brand value growthand retention system for brand drugs commercialized by brand drug advertisers through a brand drug's lifecycle during patent exclusivity and after loss of exclusivity. The brand value growth and retention system iteratively analyzes combined computational models of consumer, healthcare provider retailer and payor segment data to produce brand drug promotional campaigns that are predictive with modifying parameters that transform the promotional campaigns over time. As a result, the brand drug promotional campaign generates an increased number of brand drug purchases while predicting the pointwhere incremental promotional campaign investments produce a diminishing number of incremental brand drug purchases.

Abstract: Systems and methods for computer-implemented patient assistance are disclosed. In certain embodiments, the invention contemplates receiving patient data from plurality of sensors at a patient computer, transmitting patient data to a server, monitoring and analyzing the patient data at the server, and outputting recommended actions from the server to a personnel computer. The recommended actions are calculated based on safety considerations, emotional considerations, and/or a patient's treatment plan.

Abstract: A device for calculating a therapeutic remedy result, the device including a display; a sensor; and a computing device in communication with the display and the sensor, wherein the computing device is configured to record a user vibrancy datum; identify a therapeutic remedy instruction set as a function of the user vibrancy datum, wherein the therapeutic remedy instruction set comprises a therapeutic remedy; and calculate a therapeutic remedy result that associates the user vibrancy datum and the therapeutic remedy with a therapy response curve.

Abstract: Methods and apparatus of a smart electronic health records platform for veterinarians and human providers are disclosed. The platform integrates clinical IT systems with patient tracking whiteboards, billing processes and artificial intelligence software to increase efficiency of the patient treatment process. By aggregating many services into one platform, interaction and communication between clinics and patients will be enhanced and streamlined.

Abstract: Image based and network controlled, security systems and methods are disclosed herein for securely dispensing pharmaceutical products onsite at a physical location. A server receives scanned prescription image corresponding to a prescription of a user and determines a pharmaceutical product and a pharmaceutical product amount of the pharmaceutical product. The server receives, from a pharmaceutical product imaging device positioned within a physically secured pharmacy area, images of the pharmaceutical product, and then transmits, to a visualization user interface application executing on a network computer positioned outside the physically secured pharmacy area, a visual confirmation of the pharmaceutical product and the pharmaceutical product amount.

Abstract: Technical solutions for classifying patients with respect to multiple cancer classes are provided. The classification can be done using cell-free whole genome sequencing information from subjects. A reference set of subjects is used to train classifiers to recognize genomic markers that distinguish such cancer classes. The classifier training includes dividing the reference genome into a set of non-overlapping bins, applying a dimensionality reduction method to obtain a feature set, and using the feature set to train classifiers. For subjects with unknown cancer class, the trained classifiers provide probabilities or likelihoods that the subject has a respective cancer class for each cancer in a set of cancer classes. The present disclosure thus describes methods to improve the screening and detection of cancer class from among several cancer classes. This serves to facilitate early and appropriate treatment for subjects afflicted with cancer.

Abstract: A system and a method for transmitting an electronic prescription on the basis of cloud computing. The cloud-based electronic prescription transmission method includes the steps of: requesting an electronic prescription from a hospital server, when a cloud server receives a request for the electronic prescription, by the cloud server; extracting patient information and prescription information stored in an EMR DB, by the hospital server; converting the prescription information according to a unique API, by an API builder unit; and authenticating the converted prescription information through an electronic signature of the clinic, encrypting the converted prescription information, and transmitting the electronic prescription to the cloud server, by the hospital server.

Abstract: To identify relevant action items (that may ultimately be reflected as claims data) for closing an identified gap in care reflected by combinations of disparate claims data records within a claims data store, a task-based interventional system executes rule-based models to determine action items eligible for closing a particular gap in care identified based on criteria associated with one or more programs. The task-based interventional system executes one or more machine-learning models to generate care scores associated with relevant entities associated with the identified gaps in care and generates a task data object comprising data indicative of an action item to close the gap in care together with executable jobs for initiating computer-based workflows to provide data indicative of the gap in care to relevant entities.

Abstract: A medical software application is configurable to allow different specialty views to be specified for healthcare practitioners having different characteristics (e.g. specialists in different fields), based on, for example, role or specialty information for a logged in user. A specialty view is further be configured to affect the display of data within a domain. A specialty view can specify that a certain vocabulary takes priority for display purposes (e.g. display ordering).

Abstract: Systems and methods for surfacing contextually relevant data into the workflow of a third party system are discussed herein. The system implements a near-real-time method of detecting activity corresponding to particular electronic health records associated with particular patients in third-party systems using specifically configured software systems. A cloud-based micro-services architecture is communicably coupled to the third-party systems and is operable to transmit contextually relevant data to the third-party system in response to particular detected activities, such as accessing a patient's electronic health record. The contextually-relevant data is identified by comparing electronic health record data from various third-party systems, each third-party system associated with the particular patient, to determine gaps in the records. The contextually relevant data is transmitted to the third-party system and visually integrated into the third-party system's pre-existing clinical workflow.

Abstract: A method of screening participants for a clinical trial by obtaining identifying information chosen from a biometric sample, personal information, physical attributes, and combinations thereof from a prospective participant, optionally generating a unique identifier code, populating a database server with the unique identifier code and participant information and storing the information on non-transitory computer readable media, screening the participant for a clinical trial based on either the unique identifier code and/or participant information and searching for a match with existing participant information in the database server and a plurality of outside databases to determine protocol violations, and determining eligibility of the participant for the clinical trial and preventing the protocol violations. A system for screening participants for a clinical trial and preventing future violations while currently enrolled in a clinical trial.

Abstract: A method of predicting a healthcare event includes: receiving via an input device, classifying personal information for each of a plurality of persons; collecting measurements of at least one health indicator during a predefined learning period; creating a personal physiological pattern profile, based on the collected data; associating each of the plurality of persons to a physiological cluster based on each person's personal physiological pattern profile and based on the classifying personal information of each of the plurality of persons; creating, for each physiological cluster, a health indicator deviation pattern for the healthcare event; continuously monitoring values of the health indicator of the person; and determining an occurrence probability of the healthcare event when the monitored indicators deviate from the personal physiological pattern profile. A system for predicting a healthcare event is also disclosed.