Abstract: A breathing assistance system includes a control unit configured to be connected to a device, the device configured to provide breathing assistance to a patient, the control unit configured to simultaneously control parameters that include a pressure of air supplied to the patient, and at least one of a volume and a flow rate of the air.

Abstract: A ventilation device includes a mechanical ventilator (10), respiratory sensors (30, 32) configured to acquire measurements of respiratory variables including at least measurements of airway pressure and airway flow, and an electronic processor (14) programmed to perform a ventilation method including: operating the mechanical ventilator to provide mechanical ventilation controlled using measurements acquired by the respiratory sensors; performing a pause maneuver comprising closing at least one of an inhalation valve (38) and an exhalation valve (40) for a pause interval and estimating a respiratory mechanics index from one or more respiratory system parameters estimated from measurements acquired by the respiratory sensors during or after the pause interval; and triggering a pause maneuver in response to detecting a change in the estimated respiratory mechanics index.

Abstract: A system for evaluating a kidney includes a processing device including an input module configured to acquire patient information, the patient information including at least one of demographic data, diagnostic data, physiological data and intervention data. The processing device also includes an evaluation module, which is configured to input patient class data to an initial kidney model, the initial kidney model configured to simulate a physiological response of a kidney and configured to simulate fluid and solute transport through one or more spatial locations of the kidney. The evaluation module is also configured to input patient data corresponding to an individual patient and calculating a model response, and adjust at least one parameter of the initial kidney model based on a comparison of the patient data and the model response to personalize the initial kidney model for the individual patient.

Abstract: Disclosed herein are approaches for monitoring a patient in real-time for ARDS development and providing a biomarker-driven ventilation therapy recommendation tool based on the correlation of various therapy patterns and an ARDS biomarker score. When the ARDS biomarker indicates that a patient has a high ARDS risk, the recommendation tool suggests possible therapy routes based on clinical practice. In response to a high score output by the ARDS detection model, the tool outputs a recommendation to initiate a lung protective ventilation strategy (Low Tidal Volume, high Positive End-Expiratory Pressure (PEEP)). A high ARDS score is recognized to be predictive of the appropriateness of such therapy up to several hours before such intervention is typically initiated under current clinical practices.

Abstract: A system for assessing kidney health includes a processing device including an input module configured to receive input values related to kidney function of a patient, and a prediction module having a computation algorithm and/or a model configured to predict a kidney condition and calculate a kidney health score related to at least one of a severity and a probability of the predicted kidney condition, the kidney health score calculated based on the one or more input values. The system also includes an output module configured to present the predicted kidney condition and the kidney health score to a medical professional.

Abstract: A ventilation device includes a mechanical ventilator (10), respiratory sensors (30, 32) configured to acquire measurements of respiratory variables including at least measurements of airway pressure and airway flow, and an electronic processor (14) programmed to perform a ventilation method including: operating the mechanical ventilator to provide mechanical ventilation controlled using measurements acquired by the respiratory sensors; performing a pause maneuver comprising closing at least one of an inhalation valve (38) and an exhalation valve (40) for a pause interval and estimating a respiratory mechanics index from one or more respiratory system parameters estimated from measurements acquired by the respiratory sensors during or after the pause interval; and triggering a pause maneuver in response to detecting a change in the estimated respiratory mechanics index.

Abstract: A system and method for extracting information on infiltrates from an imaging report, and applying the report infiltrate information to clinical guidelines and clinical support applications. The system and method perform the steps of receiving the imaging report; parsing the report for infiltrate-related keywords; classifying the report based on the infiltrate-related keywords and at least one of directional words indicating a location of the infiltrates, negation words, and words canceling the negation words; presenting the classified report on a dashboard for clinical decision-making; and applying the classified report in a real-time clinical application.

Abstract: A process and system for determining a minimal, ‘pruned’ version of the known ARDS model is provided that quantifies the risk of ARDS in terms of physiologic response of the patient, eliminating the more subjective and/or therapeutic features currently used by the conventional ARDS models. This approach provides an accurate tracking of ARDS risk modeled only on the patient's physiological response and observable reactions, and the decision criteria are selected to provide a positive prediction as soon as possible before an onset of ARDS. In addition, the pruning process also allows the ARDS model to be customized for different medical facility sites using selective combinations of risk factors and rules that yield optimized performance. Additionally, predictions may be provided in cases with missing or outdated data by providing estimates of the missing data, and confidence bounds about the predictions based on the variance of the estimates.

Abstract: Disclosed herein are approaches for monitoring a patient in real-time for ARDS development and providing a biomarker-driven ventilation therapy recommendation tool based on the correlation of various therapy patterns and an ARDS biomarker score. When the ARDS biomarker indicates that a patient has a high ARDS risk, the recommendation tool suggests possible therapy routes based on clinical practice. In response to a high score output by the ARDS detection model, the tool outputs a recommendation to initiate a lung protective ventilation strategy (Low Tidal Volume, high Positive End-Expiratory Pressure (PEEP)). A high ARDS score is recognized to be predictive of the appropriateness of such therapy up to several hours before such intervention is typically initiated under current clinical practices.

Abstract: Methods and systems for selecting a cohort group or a patient at risk from a population of patients with mild cognitive impairment. The methods include using a computer configured to perform the steps: receiving normalized learning data from a portion of the population of patients; tuning a set of decision trees on the normalized learning data; receiving patient data from one or more patients of the population, wherein the patient data is independent from the learning data; classifying the patient data with the tuned set of decision trees to obtain patient threshold values; and displaying the patient threshold values.

Abstract: Using a computer communicating with an electronic medical record (EMR) system, an update in a patient EMR is automatically detected of a physiological parameter that is an input to an illness staging or evaluation clinical guideline. Responsive to detecting of the update of the physiological parameter, instructions are executed using the computer to evaluate the illness staging or evaluation clinical guideline using the updated physiological parameter as an input to the illness staging or evaluation clinical guideline to generate a guideline result. The guideline result is plotted as a function of time on a display device.

Abstract: A system for improving workflow including one or more clinical data sources which collect patient data from a patient. A patient information system stores the patient data. A clinical decision support system including one or more processors programmed to receive the patient data from the patient, generate quantified information based on a statistical model for each type of patient data, diagnose the patient based on the quantified information, generate a recommendation based on the diagnosis and the quantified information, and display the recommendation.

Abstract: A clinical decision support system (16) monitors one or more patients. The system (16) includes one or more processors (84) programmed to receive patient data for the patients. For each patient, one or more monitoring rules are selected from a plurality of monitoring rules based on patient data availability and/or patient context. A determination is made as to whether a patient is deteriorating using the selected monitoring rules for the patient. In response to determining the patient is deteriorating, an alert is generated.

Abstract: Methods and systems for selecting a cohort group or a patient at risk from a population of patients with mild cognitive impairment. The methods include using a computer configured to perform the steps: receiving normalized learning data from a portion of the population of patients; tuning a set of decision trees on the normalized learning data; receiving patient data from one or more patients of the population, wherein the patient data is independent from the learning data; classifying the patient data with the tuned set of decision trees to obtain patient threshold values; and displaying the patient threshold values.