Abstract: Automatically generating a structured medical note during a remote medical consultation using machine learning. A provider tele-presence device may receive audio from a medical provider. A medical documentation server may be coupled to the network. A machine learning network receives audio data from the provider tele-presence device, the machine learning network generating a structured medical note based on the received audio data, and wherein the structured medical note is stored in the medical documentation server in association with an identity of a patient.

Abstract: Conventionally, it has been necessary to collect blood of a subject and perform biochemical analysis to measure LDL cholesterol and HDL cholesterol. However, in this method, a needle or the like needs to be invasively inserted into the skin of the subject, which causes a psychological or physical burden on the subject. According to the present invention, it is possible to non-invasively estimate cholesterol based on attribute information and/or non-invasive biological information of a predetermined user by generating a cholesterol estimation model by machine learning based on attribute information, non-invasive biological information, and blood examination data acquired from a plurality of subjects in advance.

Abstract: Systems and methods facilitate the planning and performance of hip and other surgeries. A computer model of a hip may be generated and displayed. A template of a hip component that replaces a native portion of the hip may be superimposed on the model. Changes in leg length, offset, or anterior-posterior (AP) position as well as a virtual distance between a landmark on the model and a location on the template may be determined. During surgery, a physical distance corresponding to the virtual distance may be obtained. The template may be moved relative to the model to match the physical distance, and new change values in leg length, offset, or anterior-posterior (AP) position may be determined. The new change values may be evaluated, and the surgery may proceed, or the process may be repeated using templates corresponding to alternative components.

Abstract: A system of machine learning (“ML”) models for making actionable predictions regarding a low-incidence event, including a predictive ML model that has been trained on an augmented training data set comprising synthetic minority-class records to produce a prediction and a certainty ML model that produces a certainty estimate. A method of applying ML models to make an actionable prediction, including training a predictive ML model to make a prediction regarding a low-incidence event from a medical record, applying the predictive ML model to medical records to produce a prediction, and applying a certainty model to generate a certainty estimate. The low-incidence event may comprise risk of opioid use disorder.

Abstract: A user interface that includes a plate map that automatically updates to provide indicia descriptive of parameter assignments and parameter groups can provide an intuitive system for building experiments. For example, a user may provide one or more inputs to generate and assign a parameter setting to a plurality of cells that represent a plurality of wells. The user interface may update the plate map to depict one or more indicia to indicate which wells have been assigned the new parameter setting.

Abstract: A computer-implemented method, computer-system and computer-program product for generating medical training data for training artificial-intelligence (AI) algorithms for supporting clinical reporting and documentation are described. To generate the training data medical image data of a patient comprising medical image data elements are received and a medical findings report is generated, edited and/or received that summarizes individual medical findings. It comprises machine-readable findings-report elements the contents of which comprise semantic features. The contents of the findings report elements are automatically assigned to unique identifiers, wherein each identifier uniquely represents the medical semantic content of exactly one individual medical finding.

Abstract: Methods and systems including computer programs encoded on computer storage media, for a method for detecting signals related to subjects participating in a clinical trial. In some implementations, a computer collects clinical data from multiple sources. The computer standardizes and redacts personally identifiable information and determines predictive features that correspond to characteristics of the data that correlate with efficacy and safety signals. The computer obtains training data and trains machine learning models to predict one or both of a predicted efficacy signal and a predicted safety signal for a subject. The computer receives clinical data for a particular clinical trial subject enrolled in an ongoing clinical trial and predicts one or more signals and receives a review of the signals through a user interface. The computer updates the predictive components of the system based on the review.

Abstract: An information processing device of this embodiment includes a communication unit configured to communicates with a first terminal device and a second terminal device, the first terminal device being held by a medical caregiver, the second terminal device being held by a care assistant and a processing unit configured to acquire a medical information and a care assistance information, the medical information including a first method how to deal with a diagnosis of a patient taken by the medical caregiver, the care assistance including a second method how to deal with a status of the patient taken by the care assistant through the communication unit, wherein the processing unit is configured to provide the medical information and the care assistance information in association with the patient on the first terminal device and the second terminal device.

Abstract: This patent disclosure provides various embodiments of combining multiple modalities of non-text surgical data in forms of videos, images, and audios in a meaningful manner so that the combined data can be used to perform comprehensive data analytics for a surgical procedure. In some embodiments, the disclosed system can begin by receiving two or more modalities of surgical data during the surgical procedure. The system then time-synchronizes the two or more modalities of surgical data to generate two or more modalities of time-synchronized surgical data. Next, the system converts each modality of the time-synchronized surgical data into a corresponding array of values of a common format. The system then combines the two or more arrays of values to generate a combined set of values. The system subsequently performs comprehensive data analytics on the combined set of values to generate a surgical decision for the surgical procedure.

Abstract: In the present invention, a useful function suitable for the usages tatus of a medical device is recommended without burdening a user with advanced and complicated work for effectively using various functions installed int the medical device. This function recommendation system, which recommends functions that can be executed by a medical device 102 to a user, comprises an operation information recording unit 103 that stores operation information indicating the usage status of a medical device 102, a function information recording unit 104 that stores function information including usage conditions for recommending functions to be executed by the medical device 102, and a recommended function calculation unit 111 that outputs functions corresponding to the usage conditions as recommended functions on the basis of the operation information and the usage conditions.

Abstract: A medical system includes an issuer configured to issue data of an electronic prescription relating to a medicine prescribed to a patient and instruct a history management system for recording a token delivery history to issue a token that is information of a delivery target relating to the electronic prescription, and a controller configured to instruct the history management system to deliver the token to a terminal of a recipient of the medicine.

Abstract: A method performed by a surgical system. The method includes receiving 1) a video stream captured by a camera inside an operating room and 2) an audio stream that includes sounds captured by a microphone inside the operating room. The method detects an audio event within the operating room by performing an acoustic analysis upon the audio stream. The method produces a timestamp based on the detected audio event and based on an internal clock of the electronic device and tags the timestamp to the video stream and the audio stream. The method stores the tagged image stream and the tagged audio stream in memory.

Abstract: A method and system for initiating message listening and routing message content to authorized user devices is disclosed. For a second user device to receive notifications regarding records of a first user, the second user device provides information identifying the first user to a notification service. The notification service verifies the identifying information. The notification service initiates one or more listeners to listen for messages flowing over a messaging bus that are relating to the first user. Once a message is identified, at least a portion of the message is used to generate a notification that may be sent to the second user device.

Abstract: Techniques for improved data services are provided. A check-in scan indicating a user device in a medical facility is received, and a medical professional associated with the user device is identified. A patient of the medical facility is identified based at least in part on the check-in scan. Access permission of the medical professional is validated, with respect to the patient, based at least in part on the check-in scan. In response to validating the access permission of the medical professional, credentials of the medical professional are not requested, a patient profile of the patient is automatically retrieved via one or more networks, and input describing the patient, from the medical professional, is automatically stored in the patient profile via the one or more networks.

Abstract: A mining method for sample grouping is provided. The method includes the following steps. A field dataset including multiple samples is obtained, and each sample corresponds to an actual labeled result. The samples are respectively input to an existing model, so as to obtain the estimated results. An outlier sample set in the field dataset is removed based on a difference distribution of the estimated results and the actual labeled results, and the samples that remain in the field dataset form a remaining sample set. The remaining sample set is grouped into a hard sample set and an easy sample set based on the estimated results of the remaining sample set.

Abstract: Example methods, apparatus, and articles of manufacture to estimate costs of prescriptions are disclosed herein. An example system to estimate a cost of a prescription for a medication includes receiving a prescription for a medication for a patient, receiving a request for an estimated cost for the prescription for the patient from an entity, forming an input vector including prescription information for the received prescription and payor information for the patient, processing the input vector for the received prescription with a trained machine learning model to determine the estimated cost of the medication for the patient, updating the machine learning model based upon computed differences between predicted costs determined by the machine learning model and actual sold costs for the plurality of sold prescriptions, providing the estimated cost to a user device, and deploying the updated machine learning model.

Abstract: Apparatus and method for generating pseudo-EGM data from ECG data are disclosed. The apparatus includes at least a processor and a memory communicatively connected to the at least a processor, wherein the memory contains instructions configuring the at least a processor to generate EGM model training data, wherein generating the EGM model training data includes receiving the EGM model training data, wherein the EGM model training data includes exemplary ECG data correlated to exemplary EGM data and time synchronizing the exemplary ECG data and the exemplary EGM data, train an EGM machine-learning model using the EGM model training data, receive subject data, wherein the subject data includes subject ECG data and generate subject EGM data as a function of the subject ECG data using the trained EGM machine-learning model.

Abstract: The system brings together patient data both clinical records and imaging studies from disparate sources to the user workstation or mobile device in real-time and on-demand. In order to do so, the system needs to establish application layer connectivity utilizing HL7 or FHIR and DICOM for imaging. Once a secure connection is established, the system is able to search and retrieve records and present it to end user.

Abstract: Techniques for obtaining materials science properties of soft tissue for use in a damage model for ameliorating injuries in an individual performing a process are presented. The techniques can include obtaining physical parameters characterizing the soft tissue of the individual under each of a plurality of loading conditions, fitting a soft tissue damage model based on the parameters, and ameliorating injury in performing the process by implementing guidelines based on the soft tissue damage model.

Abstract: The present application provides a personal supplement supply system that includes: a delivery device, which further includes a housing having a plurality of cartridges removably attached to a base located within the housing. Each of the plurality of cartridges store therein at least one dispensable ingredient. The device includes a processor coupled to computer memory, the computer memory having software stored thereon that when executed causes the delivery device to dispense the at least one dispensable ingredient from each of the plurality of cartridges in accordance with a bio-informed plan personalized for a user of the delivery device.