Abstract: A digital communication module for transmission of data from a medical device is disclosed. In an example, a digital communication apparatus includes an input interface configured for communicative coupling to a medical device and an output interface configured for communicative coupling to a medical network. A processor of the digital communication apparatus receives a configuration file that specifies one input port of the input interface and at least one output port of the output interface, a first data format, and a second data format. The processor installs drivers for the input and output ports specified by the configuration file, provisions the input interface with the specified input port to receive medical data from the medical device in the first data format, and provisions the output interface with the at least one specified output port to transmit the received medical data using the first data format and the second data format.

Abstract: The present disclosure provides platforms, systems, media, and methods for capturing clinical cases and expert-derived treatment rationales to facilitate biomedical decision making, which can include virtual clinical trials that continuously learn from the experiences of all patients, on all treatments, and all the time. Algorithms such as Bayesian machine learning methods can be applied to coordinate such virtual trials.

Abstract: Systems and methods for a patient authorized medical information storage and access system. One of the methods includes receiving information indicating a transaction is to be performed between two entities, the transaction indicating an event associated with transfer or receipt of medical information; accessing a patient master index to confirm that the two entities are authorized to transfer or receive the medical information; causing generation of a blockchain transaction between the two entities; updating the patient master index to reflect the transaction; and enabling access, by a receiving entity of the two entities, to the medical information.

Abstract: Systems and methods for integrating a plurality of healthcare software applications. A user initiates one or more software applications required to perform different parts of a healthcare task. The software applications include a local application installed on the user's device and a web-based application accessed through a browser. A host application is launched in order to facilitate local two-way communication between the local application and the web-based application. The host application generates a local communication server on the user device through which the local application and web application communicate. This allows a user to easily and efficiently perform multiple parts of the healthcare tasks. This also allows different healthcare software applications to be integrated without requiring any plug-ins or other integration components to be installed on the user's device.

Abstract: Techniques for remote monitoring of a patient and corresponding medical device(s) are described. The remote monitoring comprises providing an interactive session configured to allow a user to navigate a plurality of sub sessions, determining a first set of data items in accordance with a first subsession, the first set of data items including the image data, determining a second set of data items in accordance with a second subsession of the interactive session, determining, based at least in part on the first set of data items and the second set of data items, an abnormality, and outputting a post-implant report of the interactive session.

Abstract: Systems, methods, and storage media useful in a computer healthcare system to consume clinical quality language queries in a programmatic manner are disclosed. Exemplary implementations may: load a CQL query from a third party; transform the CQL query to a modified structured query language query; load medical data elements from a database record store for each patient in one or more defined patient populations; execute the modified SQL query on medical data elements from the database record store for each patient in one or more defined patient populations; and load results of the modified SQL query.

Abstract: Systems and methods for three-dimensional dose prediction and treatment planning using a deep learning fully convolutional neural network are disclosed.

Abstract: A computer-implemented medical system is provided. The system includes a docking station and a mobile machine. The system is configured to perform operations comprising: receiving, by the mobile machine and from a user, a request to transport the mobile machine to a target location to perform a medical treatment; automatically navigating the mobile machine to the target location; performing, by the mobile machine, the medical treatment on a patient; determining, by the mobile machine, that the medical treatment is completed and the mobile machine is disconnected from the patient; automatically navigating the mobile machine to a stationary docking station of the medical system; and determining that the mobile machine is connected to the docking station through one or more connectors, and in response, receiving, by the mobile machine, at least one of an electrical charge, a refill of one or more supplies, a cleaning, or a drain of waste.

Abstract: Disclosed herein are systems and methods for identifying radiation therapy treatment data for different patients, such as field geometry. A central server collects patient data, radiation therapy treatment planning data, clinic-specific rules, and other pertinent treatment/medical data associated with a patient. The server then executes one or more machine-learning computer models to predict field geometry variables and weights associated with the patient's treatments. Using the predicted variables and weights, the server execute a clinic-specific set of logic to identify suggested field geometry, such as couch/gantry angles and/or arc attributes. The server then monitors whether end users (e.g., medical professionals) revise the suggested field geometry and trains the model accordingly.

Abstract: A method is provided for clustering data elements to extract specific patterns. The method specifies some data elements with a uniform distribution as a mini-batch and performs a single-pass cluster initialization by selecting a respective data element from the mini-batch as a respective initial cluster center to obtain cluster centers for clusters. The method assigns each data element in the mini-batch to a closest cluster by calculating a distance between each of the data elements in the mini-batch and each of the clusters. The method assigns k-minimum new centers by calculating an averaged distance to each data element in a same cluster. The method repeats the specifying step and the assigning steps responsive to a dissatisfaction of loop stop criteria which is based on distances between the centers and the K-minimum new centers. The method outputs a cluster id sequence responsive to a satisfaction of the loop stop criteria.

Abstract: A resource management system for better operation of a plurality of devices. The system comprises an input interface (IN) for receiving input data including one or more characteristics of at least one work object (P1-P3) and/or including context data. The at least one work object (P1-P3) can be processed by one or more processing devices (Mij). The said processing is specified in a respective work specification (S1-S3). A predictor component (PC) of the system is configured to predict, based on the input data, a change to the work specification. The system comprises an output interface (OUT) for providing output data that represents said predicted change.

Abstract: Techniques for solving a radiotherapy treatment plan optimization problem are provided. The techniques include receiving a radiotherapy treatment plan optimization problem; processing the radiotherapy treatment plan optimization problem with a machine learning model to estimate one or more optimization variables of the radiotherapy treatment plan optimization problem, wherein the machine learning model is trained to establish a relationship between the one or more optimization variables and parameters of a plurality of training radiotherapy treatment plan optimization problems; and generating a solution to the radiotherapy treatment plan optimization problem based on the estimated one or more optimization variables of the radiotherapy treatment plan optimization problem.

Abstract: The present disclosure relates to a method for configuring a medical device. The method comprises: providing a set of one or more parameters for configuring the medical device. Each parameter of the set has predefined values. A set of values of the set of parameters may be selected from the predefined values. Using the selected values the set of parameters may be set, which results in an operational configuration of the medical device. The medical device may be controlled to operate in accordance with the operational configuration, thereby an operating status of the medical device may be determined. Based on at least the operating status the operational configuration may be maintained or the selecting, setting and controlling may be repeatedly performed until a desired operating status of the medical device can be determined based on the operating statuses resulting from the controlling.

Abstract: A method and system is provided for assisting a user to assign a label to words or spans of text in a transcript of a conversation between a patient and a medical professional and form groupings of such labelled words or spans of text in the transcript. The transcript is displayed on an interface of a workstation. A tool is provided for highlighting spans of text in the transcript consisting of one or more words. Another tool is provided for assigning a label to the highlighted spans of text. This tool includes a feature enabling searching through a set of predefined labels available for assignment to the highlighted span of text. The predefined labels encode medical entities and attributes of the medical entities. The interface further includes a tool for creating groupings of related highlighted spans of texts. The tools can consist of mouse action or key strokes or a combination thereof.

Abstract: Disclosed is an information and data logging system for use in a dental environment. The dental environment comprising a dental unit including a number of individual selectable dental instruments and at least one instrument control unit for controlling the operation of a selected dental instrument. The information and data logging system comprises: a processing unit; and one or more displays for displaying information related to a dental treatment and one or more input units, both the one or more displays and the one or more input units being operatively connectable to said processing unit. The processing unit is configured to enable a user to select using the one or more input units a selected alternative sequence of steps of one or more alternative sequences of steps.

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: 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: 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: Systems and methods are disclosed that access over a network a set of codes and respective code descriptions from a first data store. Course data for courses is accessed over a network from a second data store. Code descriptions and course data are compared, and the comparison is used to generate a mapping of courses to codes. The network interface is used to access codes associated with patient records for a plurality of patients from an electronic medical record system associated with a medical service provider. Relevancy values are calculated for codes using the codes associated with patient records. The calculated relevancy values and the accessed mapping of courses to codes are used to generate a first ranked presentation of recommended courses. A course selection is detected. Using the selection, a second ranked presentation of recommended courses is generated by a learning engine with updated learning engine weights.