Abstract: Method and systems for creating clinical data files with secured medical information. A clinical data file may be created by converting clinical data to a single format, and the medical information may be entered into corresponding data fields in the clinical data file. The medical information may include treatment professional information, patient personal information, and/or patient image(s). Each of the data fields may be associated with an indicator, where the indicator, when enabled, may be configured to secure at least a portion of the medical information in the corresponding data field. The secured clinical data file may be configured such that, once a pass code is entered, the patient image(s) are modifiable by the addition of modification(s) that are arranged as layer(s) saved separately from the patient image(s).

Abstract: A system for evaluating mental health of patients includes a memory and a control system. The memory contains executable code storing instructions for performing a method. The control system is coupled to the memory and includes one or more processors. The control system is configured to execute the machine executable code to cause the control system to perform the method: A selection of answers associated with a patient is received. The selection of answers corresponds to each question in a series of questions from mental health questionnaires. Unprocessed MRI data are received. The unprocessed MRI data correspond to a set of MRI images of a biological structure associated with the patient. The unprocessed MRI data is processed to output a set of MRI features. Using a machine learning model, the selection of answers and the set of MRI features are processed to output a mental health indication of the patient.

Abstract: In some aspects, a method of using a virtual medical assistant to assist a medical professional, the virtual medical assistant implemented, at least in part, by at least one processor of a host device capable of connecting to at least one network is provided. The method comprises receiving free-form instruction from the medical professional, providing the free-form instruction for processing to assist in identifying from the free-form instruction at least one medical task to be performed, obtaining identification of at least one impediment to performing the at least one medical task, and inferring at least some information needed to overcome the at least one impediment.

Abstract: A respiratory system and method comprise a tracker module adaptable to be secured to a variety of inhalers, the tracker module sensing activation of the medication canister of the inhaler for delivery of medication to a user. The tracker module also senses the rate of inhalation air flow of the user when inhaling medication for determination of proper inhaler use. Upstream and downstream sensors provide flow information to determine quality of the inhalation. Other sensors are provided that monitor user presence at the inhaler, user technique in using the inhaler, and the attitude of the inhaler when it was used. Low power devices are used to conserve battery power.

Abstract: The disclosed technology provides a system and a computer implemented method for crisis state detection and intervention of a person or group of persons, the method comprising: providing a computer system designed to detect and intervene non-normal, elevated crisis operating states; using one or more biometric sensors that ascertains a crisis state via physical, behavioral, or mental indicators; deducing, with computational hardware, the operational state of a user or users from one or more biometric sensors; and administering an immediate, dual intervention of a sensory form to de-escalate the crisis operating state of a person or group of persons.

Abstract: The present invention HUB relates generally to a collection of digital health hubs (HH) with artificial intelligence and wireless connectivity to autonomously communicate with each other to create a fully automated digital health social network, that can operate both autonomously with no interaction from human element, as well as through multiple layers of outside individuals and care facilities, including but not limited to family members, caregivers and medical care providers. The present invention HUB performs various tasks to monitor, record, diagnose and communicate health and safety of individuals. The HUB additionally triages users and analyzes their recorded health data to autonomously create public and private social groups, communicate packets of general and detailed information on their users' database within HH groups. HHs can join (dock into) or exit (un-dock) from one or more public or private social HH groups.

Abstract: One embodiment provides a method including receiving natural language speech from a user. The method includes automatically converting the natural language speech into a text format and executing a function corresponding to the function portion of the natural language speech. The method includes translating data returned by executing the function into natural language, wherein the translating includes modifying sensitive information within the data returned by (i) changing a selected audible output device and output volume to prevent the at least one unauthorized user from hearing the data returned and (ii) modifying the data returned. The method also includes outputting the natural language via an audible output device. Other aspects are described and claimed.

Abstract: An inhaler tracker module is secured to an inhaler and has an activation sensor for sensing use of the inhaler. The tracker module includes a memory for storing inhaler use data, and a communications component for wirelessly transmitting the stored inhaler use data. The tracker module is wrapped around the inhaler body and includes a pressure switch located at the top of the canister to detect a user pressing the canister into the body for inhaler use. The tracking module has a standby mode in which it remains until inhaler use or until inhaler use data is stored and it is transmitted. A pairing function is provided.

Abstract: Methods and systems for selecting a machine learning algorithm are described. In one embodiment, one or more factors to be used by a plurality of machine learning algorithms in predicting a value of a required pharmacy element of a prescription are identified, each of the plurality of machine learning algorithms are trained to predict the value of the required pharmacy element using a first subset of previously received prescriptions, respective success rates for each of the plurality of machine learning algorithms at predicting respective known values of respective known required pharmacy elements for each of a second subset of the previously received prescriptions are determined, and a first of the plurality of machine learning algorithms having a highest success rate is selected to predict the value of the required pharmacy element of the prescription for a first predetermined period.

Abstract: A method of centralized monitoring management at a centralized monitoring unit (CMU) includes receiving patient monitoring data from multiple patient monitoring devices, each providing patient monitoring data for one of multiple patients, and assigning each of the multiple patients to one of at least two monitoring technician stations. Each monitoring technician station is configured to receive and display patient monitoring data the patients assigned thereto and to present alarms for each patient to a CMU technician. A load index is calculated for each monitoring technician station based on the alarms for each patient in the group of patients assigned to that monitoring technician station. At least one patient is removed from the group of patients assigned to a first monitoring technician station of the at least two monitoring technician stations based on the load index for the first monitoring technician station.

Abstract: A movement adjustment system based on heart rates and rating of perceived exertion (RPE) feedbacks of different users is provided, including: a user client, a heart rate monitoring device, a server, and a doctor client. The user client includes an RPE self-rating module, an RPE data acquisition module, a user-side video movement display module, and a user-side data storage module. The heart rate monitoring device includes an exercise data acquisition module. The server includes a data input module, a core processor, and a video movement library. The doctor client includes a doctor-side video movement display module, a video movement sending module, and a doctor-side data storage module. The above system according to the present disclosure adjusts, based on objective heart rate feedbacks during exercise and subjective RPE feedbacks after the exercise of different users, movements of next exercise of a patient.

Abstract: A context-aware healthcare notification system determines, in response to a user device has moved within a proximity of an infusion device and within a proximity of a patient identification device associated with a patient, that the infusion pump is currently experiencing an error condition regarding an administration of medication by the infusion pump to the patient. A corrective action is determined for the error condition and a notification is provided to the user device indicating that the user device is within the proximity of the infusion device and that the infusion device is experiencing the error condition, and information regarding the corrective action. The infusion device may then be caused to adjust the administration of medication by the infusion pump to the patient.

Abstract: A system for calculating nutritional requirements in a display interface the system including a computing device configured to initiate a display interface within the computing device; retrieve an input, including an input credential, and wherein the input relates a representative profile to a nutritional requirement; generate a training set using the input; receive a meal option; calculate using a machine-learning process, a nutritional requirement of the meal option using the training set; determine the nutritional requirement of the meal option as a function of the machine-learning process; and display the nutritional requirement within the display interface.

Abstract: Systems, methods, computer-readable media for automating displays based on admissions, transfers, and discharges are provided. In embodiments, a location associated with a clinician is detected. A role associated with the clinician authenticated to a first device is determined. One or more applications associated with the clinician based on the location and the role is automatically launched on the first device. In embodiments, authentication requests from the clinician are received for a second device. A session associated with the one or more applications is suspended on the first device and resumed on the second device.

Abstract: Systems and methods are provided in which local tissue diagnostic measurements are correlated with archival local tissue diagnostic data from prior tissue analyses to supplement diagnostic measurements with tissue analysis data from prior tissue analyses having similar local tissue diagnostic data. The tissue analysis data may include information such as pathology data, outcome data, and diagnosis data. The archived local tissue diagnostic data and the tissue analysis data may be stored in a database, and employed for a wide variety of methods, involving preoperative, intraoperative, and/or postoperative phases of a medical procedure. Methods and systems are also provided for displaying, on a medical image shown in a user interface, hyperlinked reference markers associated with tissue analyses, where the reference markers are shown at locations corresponding to local tissue analyses, and where associated diagnostic data and/or tissue analysis may be viewed by selecting a given reference marker.

Abstract: A method is for adapting method steps for finding a result in a CT-based decision support method to the evaluation of LDCT image datasets. In an embodiment of the method, a plurality of reference image datasets are acquired from a plurality of patients. A reference image dataset features at least one CT image dataset from one of the plurality of patients and an LDCT dataset from the patient. Furthermore, method steps for establishing result data are applied to the different image datasets of the reference image datasets. The result data is compared with one another and the method steps for establishing result data are adapted based upon a result of the comparison to the establishing of result data with reference to an LDCT image dataset. An LDCT-based decision support method is also described. Moreover an adaptation device is described. A system for LDCT-based decision support is further described.

Abstract: Systems and methods are provided for determining an emotional state of a medical professional and dynamically generating clinical procedures that are adapted to the medical professional's emotional state, as well as an assessment of a medical device based on the determined emotional state. Observation data corresponding to a medical professional associated with a clinical procedure can be received and processed to determine an emotional state of the medical professional. The emotional state can be predicted using a first predictive model trained in a machine learning process. The determined emotional state can be provided to a second predictive model to provide one or more adapted clinical procedures. Device assessment data can also be used with the determined emotional state to determine an assessment of a medical device. The one or more adapted clinical procedures and the assessment of the medical device can be provided as an output.

Abstract: The present invention is directed to an electronic system for the assessment of emotional state. The system allows individual employees to specify their emotions using a set of emojis. The system provides a graphical user interface that displays a list of different emotions and associated emojis that the user can select. The system allows the user to write an entry about his thoughts and emotions in conjunction with the selected emojis and send the message with the emojis to individuals with whom he chooses to share. The system provides a list of company-wide employees from which the user can select. The system receives the messages and implements data structures to process the received messages and produce individual and company-wide emotional state information.

Abstract: Systems, methods, and computer-readable media are provided for identification of patients having an elevated near-term risk of chronic kidney disease progression, including quantitatively predicting whether or not an elevated risk of progression of Stage 3 or Stage 4 chronic kidney disease is likely within a time interval of up to 36 months subsequent to computing the prediction. Based on the prediction, appropriate care providers may be notified so that the risk of CKD progression may be mitigated. In some embodiments, serial measurements are obtained of urine osmolality, and a challenge with an AVP V2 antagonist and serum sodium concentration is provided. From a time series based on the serial measurements, estimates of each variable's velocity and/or doubling-time may be determined. These values then may be combined via a multivariable mathematical model for providing a leading indicator of near-term future abnormalities in kidney function.

Abstract: A diagnosis method, system, and computer program product, include processing a user input comprising medical symptoms, assigning the user to a team of physicians and a cognitive agent based on the processed medical symptoms, each of the physicians having a different medical specialty corresponding to a disease associated with the medical symptoms, and producing a consensus diagnosis from the team of physicians and the cognitive agent.