Abstract: Embodiments include methods, devices, systems, and non-transitory process-readable storage media for managing care provider coverage in a medical communication system. Some embodiments may include receiving from a first communication device associated with a first user a coverage request defining a coverage period and requesting that a second user associated with a second communication device provide care coverage for the first user, sending a notification of the coverage request to the second communication device including the coverage period and requesting agreement to provide care coverage for the first user, receiving from the second communication device an acceptance of the coverage request, and directing to the second communication device a message sent to the first communication device during the coverage period in response to receiving the acceptance of the coverage request.

Abstract: A system includes a remote control device configured to remotely control a device and a safety control device communicating with each other via a wireless connection. The remote control device includes a switch, a motion enable unit configured to generate processed information by processing information using a first secret, and a hand control unit capable of acquiring the processed information only when the switch is in a closed state and configured to transmit the processed information to the safety control device via the wireless connection. The safety control device includes a communication unit configured to receive the processed information via the wireless connection and a safety control unit configured to verify the closed state of the switch by processing the processed information using a second secret that matches the first secret and enable control of the device when the closed state of the switch is verified.

Abstract: A medical image reconstruction and transmission method employing a medical image reconstruction and transmission system according to an embodiment of the present invention includes receiving medical image data including at least one of k-space data obtained through accelerated imaging and digital imaging and communications in medicine (DICOM) data generated on the basis of the k-space data obtained through accelerated imaging, reconstructing the received medical image data using an artificial neural network model, and transmitting the reconstructed medical image data on the basis of an address from which the medical image data is received.

Abstract: Methods of using visual functions such as dark adaptation, low luminance visual acuity, low luminance deficit, contrast sensitivity and scotopic sensitivity as functional biomarkers for statin therapy in AMD. These biomarkers can be used, for example, to support clinical trials of statin therapy for AMD by identifying participants more likely to respond, by providing an early indication of response, or by serving as an endpoint; or to support treatment of AMD patients with statins by identifying patients more likely to respond, by providing an early indication of responders vs. non-responders, or by confirming a treatment benefit.

Abstract: A computing system may obtain and aggregate surgical monitoring data associated with multiple surgical procedures in multiple operating rooms (ORs), and the surgical monitoring data may be obtained via the surgical hubs in the ORs. Surgical resource utilization adjustments may be generated based on the aggregated surgical resource monitoring data, and an output may be generated based on the determined surgical resource utilization adjustment. The aggregated data may be used to generate resource allocation adjustments for the ORs. Resource allocation adjustments may include healthcare professional (HCP) assignment adjustments, surgery scheduling adjustments, surgical instrument allocation adjustments, OR layout adjustments, and/or medical facility layout adjustment(s), etc.

Abstract: Systems and methods for calculating medical claims payment estimates may receive a medical claim for a first patient including billing code(s) and demographic data, apply the demographic data to identify payer(s) for the first patient, access a data universe including patient data collection(s) of patient data records for a second group of patients, payer data collection(s) of data records for payers, and a financial history data collection including financial data record(s) for the first patient, identify, for each billing code, a payer payment pattern based on a combination of the patient data records and payer data record(s) corresponding to the payer for the first patient, identify a patient payment pattern based on the financial data record(s), and apply the payer payment pattern and the patient payment pattern to the medical claim for the first patient to calculate a payment estimation for the medical claim.

Abstract: An AI algorithm may be used in a clinical setting to perform one or more tasks to assist medical personnel. The results produced by the AI algorithm may affect not only patient care, but also the cost of the care. The AI algorithm may be trained on auxiliary data to incorporate the impacts on patient care and cost.

Abstract: A method and system provide for automated counting of prescription product and enables virtual verification of the dispensed prescription product. The method and system include capturing by a camera at a first site an image of the prescription product to be dispensed according to a prescription to a patient, electronically displaying the image on a display at a second site remote from the first site, and electronically transmitting a verification from the second site to the first site in response to the image of the prescription product being determined at the second site to be consistent with the prescription.

Abstract: The present application relates to a computer-implemented medical method of determining a patient-specific setting of at least one imaging parameter of an imaging device. The method includes acquiring patient data describing information relating to a patient and having impact on the setting of at least one imaging parameter of the imaging device and acquiring object data describing at least one property of at least one object of interest associated with the anatomy of the patient. The imaging parameter data is determined based on the patient data, describing a patient-specific setting of the at least one imaging parameter of the imaging device.

Abstract: The present invention relates to a method encompassing acquiring data as to the geometric structure/topology of a predefined surface section as well as to an additional physical property assigned to the surface section, determining variability of the geometric structure/topology as well as of the additional physical property over the surface section, and determining from these at variabilities an expected stability of co-registering datasets describing the predefined surface section. The present invention further relates to a corresponding computer program and a corresponding system for carrying out this method.

Abstract: A system for generating an entity duration value within a graphical interface, wherein the system includes at least a computing device, a display device, a memory; a processor configured to: generate a display data structure, providing a plurality of visual elements associated with a plurality of node modules and at least an event handler, wherein: a first visual element linked to a first data module of a node module of the plurality of node modules; a second visual element linked to a second data module of at least an entity duration value; the first data module is configured to: receive first data corresponding to the node utilization interval; and execute the second data module; and the second data module is configured to: modify the node utilization interval; and generate the display data structure using the plurality of visual elements and the at least an event handler.

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: An evaluation of a cancer treatment start date for a cancer medication identifies a first plurality of subjects and, for each, the treatment start date. A subject is selected for a second plurality of subjects by applying features for the subject to a model at a propensity value threshold. One subset of the features is associated with a time period and another subset is static. The applying obtains anchor point predictions, each associated with a time in the time period and including a probability that the time is the start date. The time of the anchor point prediction having the greatest probability is assigned the anchor point of the subject. The start date is evaluated with a survival objective based on the start date for each subject in the first plurality and the assigned anchor point for each subject in the second plurality.

Abstract: A telemedicine platform utilizes artificial intelligence to match patients with practitioners. The platform includes a virtual assistant operable to automatically generate responses to a patient using machine learning in order to further identify details regarding the patient's symptoms and needs. The virtual assistant includes a digitally generated human face that automatically adapts mouth-movements and facial expressions to match the automatically generated responses in order to provide a feeling of interacting with a human assistant. The platform includes a patient interface, for identifying physicians and scheduling appointments, a practitioner interface, for managing patients and scheduling issues, and an administrator interface, for managing a larger practice of multiple practitioners.

Abstract: A system and method for generating a 3D-printed medical appliance treatment plan and providing a set of 3D-printed medical appliances in accordance therewith, the method comprising: generating a dynamic 3D-printed medical appliance treatment plan generation model; obtaining a patient record; receiving 3D scanning data of the patient; generating a 3D-printed medical appliance treatment plan by applying the patient record and the 3D scanning data to the dynamic 3D-printed medical appliance treatment plan generation model; providing the 3D-printed medical appliance treatment plan to a medical practitioner; providing a manufacturing request to a manufacturer system for manufacturing a set of 3D-printed medical appliances; providing the set of 3D-printed medical appliances to the patient; receiving feedback from the medical practitioner regarding the 3D-printed medical appliance treatment plan; modifying the dynamic 3D-printed medical appliance treatment plan generation model based on the feedback.

Abstract: The invention relates to a method for determining a model of an extremity, for providing an individually designed orthosis or prosthesis, the method comprising a step of displaying at least one option for data input by a user, in particular in the form of a patient questionnaire. In a further step, the determination of at least one patient-specific input parameter takes place on the basis of the data input. In one step, the creation of at least one raw model takes place using the at least one input parameter. In a further step, the ascertaining of at least one measured parameter of the raw model and, according to one step, the visualizing, in particular displaying, of the raw model and the at least one measured parameter takes place. Furthermore, the invention relates to a computer-readable storage medium and also a system.

Abstract: Example methods for radiotherapy treatment planning using deep learning engines are provided. One example method may comprise obtaining first image data associated with a patient; generating first feature data by processing the first image data associated with a first resolution level using a first processing pathway; generating second feature data by processing second image data associated with a second resolution level using a second processing pathway; and generating third feature data by processing third image data associated with a third resolution level using a third processing pathway. The example method may also comprise generating a first combined set of feature data associated with the second resolution level, and a second combined set of feature data associated with the first resolution level based on the first feature data and the first combined set. Further, the example method may comprise generating output data associated with radiotherapy treatment of the patient.

Abstract: A system is provided for registration, check-in, and service tracking of patients. In an example arrangement, the system includes a front end system and a back end system. The front end system including one or more web servers that are configured to provide one or more web portals. The back end system is communicatively connected to the front end system. The back end system includes a data server and a processing server. The processing server configured to store patient data for scheduled appointments in the data server in a standardized format. The processing server is configured to provide access to the patient data to the one or more web portals. The one or more web portals are configured to communicate with the processing server to provide access permit the patient and staff remote access to the patient data to facilitate pre-registration, check-in, and service tracking of patients.

Abstract: Decision support technology is provided for use with patients who may be prone to a cardiovascular condition such as acute coronary syndromes. A mechanism is provided to determine a patient's risk for experiencing a cardiovascular ischemic event at a future time interval based on temporal patterns determined using physiological parameters of the patient such as serum or blood uric acid and/or C-reactive protein (CRP). A forecast or score may be determined indicating whether or not temporal patterns merit intervention to prevent occurrence or reoccurrence of ischemic events, or for determining adherence to or efficacy of treatment or preventive interventions. Based on the forecast or score, appropriate response action such as automatically issuing an alert or notification to a caregiver associated with the patient, may be determined, recommended, or implemented.

Abstract: Various methods and systems are provided for dynamically adjusting user guidance based on a user's proficiency by tracking the same. In one example, a proficiency score for a user may be tracked over time and practice based on a pre-defined rubric for a given anatomical region and a given anatomical target within the anatomical region. During medical imaging, based on the proficiency score of the user, an amount of user guidance that is provided to the user may be adjusted. For example, user guidance may be automatically activated to guide the user during the imaging procedure when the proficiency score of the user is less than a threshold score.