Abstract: Systems and methods for generating customized annotations of a medical record are provided. The system receives a medical record and processes it using a predictive model to identify evidence of a finding. The system then determines whether to have a recall enhancement or validation of a specific finding. Recall enhancement is used to tune or develop the predictive model, while validation is used to rapidly validate the evidence. The source document is provided to the user and feedback is requested. When asking for validation, the system also highlights the evidence already identified and requests the user to indicate if the evidence is valid for a particular finding. If recall enhancement is utilized, the source document is provided and the user is asked to find evidence in the document for a particular finding. The user may then highlight the evidence that supports the finding. The user may also annotate the evidence using free form text.

Abstract: Systems, methods and computer-readable media are provided for monitoring patients and quantitatively predicting whether an event such as a significant change in health status meriting intervention, is likely to occur within a future time interval subsequent to computing the prediction. Medical data for a patient is collected from one or more different inputs and used to determine time series data. From this, a forecasted numerical value is computed for one or more physiologic parameters associated with the patient, which may be used to further monitor the patient and facilitate decision making about a need for intensified monitoring or intervention to prevent or manage physiologic or hemodynamic deterioration. An evolutionary algorithm, such as particle swarm optimization and/or differential evolution, may be used to determine the most probable value of the physiologic parameter(s) at one or more future times.

Abstract: The disclosed systems and methods provide patient care unit (PCU) order confirmation. A method may include authorizing a user to operate a medication delivery device. The method may also include retrieving, in response to the authorizing, a user history associated with the user, wherein the user history includes one or more dispensing records for pending medications. The method may also include determining, based on a context that includes the user history, one or more medication order candidates for present administration. The method may also include presenting a user interface for confirming a medication order from the one or more medication order candidates. The method may also include configuring at least one parameter of the medication delivery device based on the confirmed medication order received from the user interface.

Abstract: Disclosed systems, methods, and computer readable media can diagnose a health condition based on patient time series data. For example, a method for diagnosing a health condition based on patient time series data includes identifying a training set of health records comprising a first set of patient time series data, training a neural network using the training set of health records, and executing the trained neural network model to diagnose a health condition based on a second set of patient time series data. In further examples, the first set of patient time series data and the second set of patient time series data can each comprise electrocardiogram data and the health condition can comprise pulmonary hypertension.

Abstract: Systems and devices for detecting and characterizing stratified fluid and/or aerosol particles and droplets, and methods of use thereof to, for example, diagnose and prognose respiratory diseases and disorders are provided. The systems typically include optoelectronic sensors for detecting foreign particles like bacteria and pollutants in the air (i.e., the aerosol) based on light scattering. Information collected in this way can be used to, for example, detect or identify respiratory maladies and determine the effectiveness of methods of treatment thereof.

Abstract: In clinical documentation, mere documentation of a condition in a patient's records may not be enough. To be considered sufficiently documented, the patient's record needs to show that no documentation drop-offs (DDOs) have occurred over the course of the patient's stay. However, DDOs can be extremely difficult to detect. To solve this problem, the invention trains time-sensitive deep learning (DL) models on a per condition basis using actual and/or synthetic patient data. Utilizing an ontology, grouped concepts can be generated on the fly from real-time hospital data and used to generate time-series data that can then be analyzed by trained time-sensitive DL models to determine whether a DDO for a condition has occurred during the stay. Non-time-sensitive models can be used to detect all the conditions documented during the stay. Outcomes from the models can be compared to determine whether to notify a user that a DDO has occurred.

Abstract: Systems and methods for personalizing medicine utilizing the true state of the patient are provided. A number of medical records for a patient are subjected to predictive modeling for various conditions (known as patient ‘true state’). The patient personal information, previous care, and true state may be provided into a state machine in order to determine the resources needed for the patient. The medical resources may be any of laboratory services, diagnostics, therapies and medications. Using the true state information, and number of activities may be performed for the patient based upon the patient's needs. These activities include scheduling lab or diagnostic procedures in advance of an appointment, filling in documentation gaps, identifying items that require additional documentation using the true state, and tracking follow-up. It may also be beneficial to validate the true state.

Abstract: Methods and systems for cohort selection for agile processes are disclosed. A method includes: assigning, by a computing device, each of a plurality of entities to one of a plurality of groups; and for each of the plurality of groups: for each of the entities in the group, determining, by the computing device, information about the entity and encoding the determined information about the entity using a genetic algorithm; determining a ranking, by the computing device, of each of the entities in the group based on the encoded information about each of entity in the group; crossing over, by the computing device, portions of the encoded information of pairs of entities occupying adjacent positions in the ranking; and measuring, by the computing device, fitness of each of the entities in the group.

Abstract: This invention relates to automatic medical diagnostic methods and systems. The object of the invention is to provide a method and a system of passive and fully automated nosological diagnostics. The objective is solved based on the method of the spectral-dynamic analysis of a wave signal from the body surface, recognition and assessment of the degree of matching to nosological groups of spectral-dynamic samples to determine the presence or stages of a disease. The system is made as a distributed system with multiple terminals for recording wave signals and provided with a system for transmitting them to the center for processing and establishing a diagnosis. To achieve more accurate diagnostic, a resonance and compensation biological feedback is used depending on the energetic type of active samples.

Abstract: A computer assisted surgery system includes a controller configured to display images of the surgical procedure according to a workflow plan. The controller is configured to retrieve data and determine the workflow plan based on the data. The controller may also be configured to record and store data related to the surgical procedure on, for example, a hospital network.

Abstract: A method of generating a user interface for use in documenting a patient encounter comprises: automatically identifying, with a computing device, at least one documentation protocol based on at least one element of the patient's medical record; and generating a user interface including at least one of the identified documentation protocols, the at least one identified documentation protocol identifying at least one medical finding. A system comprises a data store encoded on a memory device, the data store comprising documentation protocols. The system further comprises an input apparatus. A computing device is in data communication with the data store and the input apparatus. The computing device is programmed to receive findings input through the input apparatus, identify a documentation protocol based on the finding input through the input apparatus, and generate a user interface. The user interface comprising the identified documentation protocol.

Abstract: Disclosed is a drug compliance management method including a microneedle applicator configured to infuse a drug by means of a microneedle in the form of a wearable device, a patient terminal configured to process drug compliance information including drug infusion information received from the microneedle applicator and medication information separately input by a patient after administration, a server configured to transmit the drug compliance information received from the patient terminal, and an expert terminal configured to display drug compliance information collected from a plurality of patient terminals.

Abstract: Methods and devices are provided for healthcare action sequencing and record keeping. The method may involve scanning a patient care area for tags for entities present in the area, a given patient being located in the area. The method may involve reading identity data from a tag, in response to detecting the tag for an entity in the area. The method may involve receiving input data regarding the given patient by a healthcare personnel via a user-interface. The method may involve communicating with a management system that includes a first database storing rules for how patients with known sets of conditions are to be cared for, a second database storing rules for how the input data are to be used, and a third database storing rules relating to procedures and restrictions for the healthcare personnel.

Abstract: A system for informed selection of prescriptive therapies. The system includes a computing device configured to receive compositional training data containing a plurality of unclassified data entries. The system is configured to retrieve a user biological profile and generate an unsupervised machine-learning model that utilizes a biological profile as an input and outputs a therapy response label. The system selects a therapy response model and receives from a remote device a proposed prescriptive therapy. The system creates a therapy response model and identifies a prescriptive therapy label for a proposed prescriptive therapy.

Abstract: A method for filtering ECG data includes receiving ECG data of a patient, generating an ECG report comprising a plurality of pages, and presenting priority information on a first page of the plurality of pages. The priority information includes information identifying the patient, monitoring summary information including an indication of a total duration of a monitoring period, heart rate summary information including an average heart rate, a fastest heart rate, and a slowest heart rate, representative arrhythmia summary information including a count of ECG strips containing each of a plurality of types of cardiac arrhythmia, and atrial fibrillation summary information including an indication of atrial fibrillation burden during the monitoring period. The first page of the report does not include an ECG strip.

Abstract: A method for capturing patient feedback for a medical treatment includes: receiving user instructions indicating a symptom being treated, a symptom score for the symptom being treated, and an indication of a beginning of a treatment session; receiving patient feedback comprising an updated symptom score for the symptom being treated and/or absence or presence of one or more of a plurality of attributes; storing the received patient feedback and a time in the treatment session at which the respective patient feedback was received; repeating the receiving of patient feedback and storage of data during the treatment session; and receiving a user instruction indicating an ending of the treatment session, wherein an alerting module alerts a user of the computing device for input of patient feedback after a predetermined period of time has elapsed following receipt of patient feedback without a subsequent receipt of patient feedback.

Abstract: Examples of the present disclosure describe systems and methods for the long-term, real-time active monitoring of a wireless implant. In aspects, a wireless biosensor may be implanted in a breast biopsy cavity. The biosensor may detect biochemical parameter data of the breast biopsy cavity and the human body. The biosensor may transmit the detected biochemical parameter data in real-time to a surveillance system wirelessly coupled to the biosensor. The surveillance system may then facilitate the evaluation of the biochemical parameter data. In examples, the evaluation may comprise detecting trends in a tumors microenvironment, monitoring the progress of a treatment, or adjusting a treatment to tailor a personalized treatment.

Abstract: A virtual assistant/chatbot to improve clinical workflow for home renal replacement therapies is disclosed herein. A virtual assistant/chatbot includes a patient-facing user interface configured to enable a patient to engage in a virtual chat session by typing, speaking, or otherwise providing information regarding a patient request or issue related to their renal replacement therapy. The virtual assistant/chatbot also includes a backend server-based system configured to provide logic to respond to a patient's requests. The logic defines a sequence of questions and answers for resolving patient queries. The sequence of assistant/chatbot questions and patient answers may be configured in a node arrangement such that certain patient answers/requests lead to additional questions for additional information from a patient.

Abstract: A processor-implemented method comprises obtaining current operational context information associated with a sensing device; obtaining an expected calibration factor parameter model associated with a patient; calculating an expected calibration factor value based on the expected calibration factor parameter model and the current operational context information; obtaining one or more electrical signals from the sensing device, the one or more electrical signals having a signal characteristic indicative of a physiological condition; converting the one or more electrical signals into a calibrated measurement value for the physiological condition using the expected calibration factor value; and outputting the calibrated measurement value for the physiological condition.

Abstract: There is provided a system for tracking events associated with a treatment by personalised medicine, the system comprising a plurality of nodes hosting a blockchain. The plurality of nodes include a plurality of sequence manager nodes, each associated with a respective sequence manager contract on the blockchain, and a hub node associated with a hub contract on the blockchain. A first sequence manager contract of the sequence manager contracts is arranged to receive first event data indicating a first event associated with the treatment, and store the first event data on the blockchain in association with a first event sequence. The hub contract is arranged to store an association between the first event sequence and one or more further event sequences associated with the treatment, on the blockchain.