Abstract: A system, method, and computer-readable media are provided for facilitating clinical decision making, and in particular, decision making based on a third party's clinical situation by determining and providing useful, up-to-date information, such as patient-related information to a decision maker. In one embodiment, a user first identifies an information item concerning a patient. Based on that item, a set of related information items is determined and prioritized, and a reference pointer, which identifies the set of related information, is generated. The reference pointer is communicated to the user's mobile device. Subsequently, the user's mobile device requests information from the set of information items associated with the reference pointer, and provides information authorization information. Following authentication of the user's credentials, updates of information from the set of information items may be communicated to the user's mobile device as they become available.

Abstract: Technologies are provided for determining a likelihood or risk of a human patient for developing pressure injury based on patterns of movement by the patient determined using a specialized measurement support surface. Some embodiments automatically ascertain whether patterns of movements of a human subject, whose weight is supported on the support surface, exhibit sufficient frequency and variability of activity such as will confer either certain health benefits or expose the individual to certain health risks, such as development of pressure ulcers in the load-bearing skin and soft tissues. If the determined patterns manifest such features associated with benefits or risks, then a notification may be provided for the patient to move; for instance, to the patient or a caregiver. In some embodiments, a notification may be provided at an irregular time intervals within-day intervals.

Abstract: Technologies are provided for determining deficiencies in narrative textual data that may impact decision-making in a decisional context. A candidate text document and a reference corpus of text may be utilized to generate one or more topic models and document-term matrices, and then to determine a corresponding statistical perplexity and probabilistic coherence. Statistical determinations of a degree to which the candidate deviates from the reference normative corpus are determined, in terms of the statistical perplexity and probabilistic coherence of the candidate as compared to the reference. If the difference is statistically significant, a message may be reported to user, such as the author or an auditor of the candidate text document, so that the user has the opportunity to amend the candidate document so as to improve its adequacy for the decisional purposes in the context at hand.

Abstract: A system, methods, and computer-readable media are provided for the automatic identification of patients having an elevated near-term risk of pulmonary function deterioration or respiratory distress. Embodiments of the invention are directed to event prediction, risk stratification, and optimization of the assessment, communication, and decision-making to prevent respiratory events in humans, and in one embodiment take the form of a platform for wearable, mobile, untethered monitoring devices with embedded decision support. Respiratory information is obtained over one or a plurality of previous time intervals, to classify a likelihood of events leading to an acute respiratory decompensation event within a future time interval. In an embodiment, the risk prediction is based a plurality of nonlinearity measures of capnometry information over the previous time interval(s), and the risk for an acute respiratory decompensation event determined using an ensemble model predictor on the nonlinearity measures.

Abstract: Methods and systems for enhanced natural language processing of clinical documentation are provided. Using natural language processing, a clinical condition is extracted from unstructured data within a current electronic document. A clinical ontology identifying itemsets associated with the clinical condition is retrieved, and indicators of relevant clinical concepts, as identified from the ontology, are searched from within the patient's longitudinal record, which comprises documentation from at least a prior encounter. Based on the whether the clinical concepts are present in the patent's record, a confidence is assigned to the NLP-extracted clinical condition, and one or more actions may be performed.

Abstract: An improved decision support tool is provided for detecting (or for diagnosing or treating human patient at risk for developing) a functional gastrointestinal condition, such as irritable bowel syndrome (IBS). The decision support tool, which may comprise a smart sensor, determines microbiota diversity, relative abundances of microbial taxa, trends in the relative abundances, and concentrations of immunoglobulin G subclasses, from specimens from the subject, and combines these determined values using a classifier to automatically ascertain whether changes or trends in the values are statistically significant and clinically actionable with respect to diagnosing and managing the subject's condition.

Abstract: Systems, methods and computer-readable media are provided for facilitating clinical decision support and managing patient population health by health-related entities including caregivers, health care administrators, insurance providers, and patients.

Abstract: Methods, systems, and computer-readable media are provided for enabling improvements in athlete training and injury management through entropy and third-order spectral analysis of digitized force-vs-time time series from movements. In embodiments, entropy and/or bispectral statistics are determined using time-series information obtained from movements of an athlete, such as squat jump and countermovement jump maneuvers, using a biomechanical sensor, such as a digital force plate apparatus. These statistics may be used to facilitate sports medicine and health management of the athlete.

Abstract: Methods, systems, and computer-readable media are provided for facilitating record matching and entity resolution and for enabling improvements in record linkage. A power-spectrum-based temporal pattern-specific weight may be incorporated into record linkage methods to enhance the record linkage accuracy and statistical performance. For example, in embodiments, a value-specific weight may be calculated from a population-based frequency of field-specific values and provides an opportunity to capture and measure the relative importance of specific values found in a field. A timeseries-derived Bayesian power spectrum weight may be calculated from the population-based frequency of temporal pattern-specific values in terms of intensities at various frequencies of the power spectrum computed from the timeseries, and further provides an opportunity to capture and measure the relative importance of specific sequences of care episodes.

Abstract: Technologies are provided for an improved classifier apparatus and processes for improving the accuracy of classification technology including example applications of such classifiers. A process includes applying clustering to variables contributing to the classification task. The clusters may be represented in a 1-dimensional, 2-dimensional, or 3-dimensional matrix that is a spatial abstraction of the interrelationships. A convolutional transformation may be applied to the matrix so as to reduce the effective dimensionality of the classification problem and improve the signal-to-noise ration. A deep learning neural network method may be applied to the transformed network to generate an improved classification model, which may be utilized by a decision support tool. One embodiment comprises a decision support tool for detecting risk of venous thrombosis and venous thromboembolism (VTE) in a patient, based on phenotype and genomics information.

Abstract: Systems, methods and computer-readable media are provided for facilitating patient health care through automatic discovery, establishment, and statistical validation of diagnostic-signals in repositories of EMR information, identifying phenotypic diagnostic signals regarding markers or combinations or sequences of patient attributes. Some methods include identifying a first group of patients that have one or more markers and extracting one or more diagnostic statuses that pertain to the whole genome sequencing (WGS) or whole exome sequencing (WES). Statistically significant differences involving frequent itemsets are identified and may be used to evaluate membership of an individual in a class indicative of potential diagnosis via WGS or WES.

Abstract: Systems, methods and computer-readable media are provided for predicting candidacy for Kidney Surgery and related computer-performed decision support. In particular, embodiments of the disclosure are directed to identifying populations of patients who are candidates for vascular access placement in Chronic Kidney Disease (CKD). Some embodiments of the present disclosure provide a system and method for continually tracking the clinical and physiologic status of a patient in a hospital. At least some of the embodiments assist nephrologists in preventing and reducing the frequency of crises in urgent/emergent presentation with requirement for dialysis (“crashing onto dialysis”) by using the systems' capability to recognize patterns in a patient's eGFR and serum uric acid values before the patient deteriorates or reaches a crisis.

Abstract: Systems, methods, and computer-readable media are provided for facilitating clinical decision making by directing the emission of computer-generated health-care related recommendations towards contexts in which the recipient will likely find the recommendations salient and will likely welcome them and act upon them. ‘Uptake’ of computer-generated recommendations for diagnostic tests or therapeutic interventions is thereby substantially increased, and ‘alert fatigue’ is substantially decreased. Embodiments of our technology overcome certain drawbacks associated with the prior art by providing a means for ascertaining which decision-support recommendations are likely to be favorably considered by the recipient and acted-upon (recommendation ‘uptake’). System and method embodiments for providing a predicted probability of user uptake of a context-specific system-generated recommendation patient are disclosed herein and for applying that information to decide whether or not to emit the relevant recommendation.

Abstract: Technologies are provided for an improved classifier apparatus and processes for improving the accuracy of classification technology including example applications of such classifiers. A process includes applying clustering to variables contributing to the classification task. The clusters may be represented in a 1-dimensional, 2-dimensional, or 3-dimensional matrix that is a spatial abstraction of the interrelationships. A convolutional transformation may be applied to the matrix so as to reduce the effective dimensionality of the classification problem and improve the signal-to-noise ration. A deep learning neural network method may be applied to the transformed network to generate an improved classification model, which may be utilized by a decision support tool. One embodiment comprises a decision support tool for detecting risk of venous thrombosis and venous thromboembolism (VTE) in a patient, based on phenotype and genomics information.

Abstract: Various tools are disclosed for providing assistive or augmentative means to enhance the fluency and accuracy of persons having speech disabilities. These technologies may automatically ascertain and dynamically improve the accuracy with which automatic speech recognition (ASR) systems recognize utterances of persons having impaired speech conditions. In an embodiment, digitized audio information about a speaker’s utterance is processed to determine a set of candidate words matching the utterance. From these candidate words, a set of concepts is determined using a finite state machine model. A pictogram representing each concept is identified and presented to the speaker so that the speaker may select the pictogram corresponding to the best match of his or her intended meaning associated with the utterance. An action corresponding to speaker’s selection then may be performed. For example, displaying or synthesizing speech from textual information describing the selected concept.

Abstract: Various tools are disclosed for providing assistive or augmentative means to enhance the fluency and accuracy of persons having speech disabilities. These technologies may automatically ascertain and dynamically improve the accuracy with which automatic speech recognition (ASR) systems recognize utterances of persons having impaired speech conditions. In an embodiment, digitized audio information about a speaker’s utterance is processed to determine a set of candidate words matching the utterance. From these candidate words, a set of concepts is determined using a finite state machine model. A pictogram representing each concept is identified and presented to the speaker so that the speaker may select the pictogram corresponding to the best match of his or her intended meaning associated with the utterance. An action corresponding to speaker’s selection then may be performed. For example, displaying or synthesizing speech from textual information describing the selected concept.

Abstract: Systems, methods and computer-readable media are provided for determining the modality for transferring, lifting, or repositioning (TLR) a human patient in a health care setting contexts. In some cases, a model-based recursive partitioning and Bradley-Terry regression is applied, which may be optionally parallelized so as to determine statistical associations with various factors, such as caregiver attributes, care venue, and patient attributes. One embodiment determines a Bradley-Terry regression model from the recursive partitioning which may be incorporated into a TLR selection decision-support tool or otherwise utilized to identify the optimal modality.

Abstract: A cusp catastrophe approach is provided for predicting an occurrence of an ischemic myocardial event (e.g., acute myocardial infarction) for a human patient based on measurements of a vital sign via one or more sensors. The one or more sensors may comprise a user-wearable device. A cusp catastrophe model is used to process the vital signs measured. In some aspects, the cusp catastrophe model is used for processing a time series constructed from the vital sign measurements. In aspects, the time series may also include historical vital signs of the patient stored in an electronic health record system. A likelihood of the patient experiencing a myocardial ischemia occurrence is determined based on an output of the cusp catastrophe model satisfying a threshold. Based on the likelihood determined, a response action is initiated.

Abstract: Systems, methods and computer-readable media are provided for facilitating clinical decision support and managing patient population health by health-related entities including caregivers, health care administrators, insurance providers, and patients.

Abstract: An improved decision support tool is provided for detecting and treating human patients at risk for having (or developing) venous thromboembolism VTE. The tool determines a quantitative probability of VTE by utilizing a smart sensor based on a particular machine-learning model for detecting specific biomarkers determined to be related to VTE. In particular, a quantitative probability of VTE may be determined via a model based on interrelationships between multiple components of the human body's complement cascade and their coupling to coagulation processes. In one aspect, a quasi-Dirichlet distribution “mixture” relationship between total hemolytic complement (CH50) activity and complement protein C3 levels is employed as part of a smart sensor and decision support tool to provide predictive, diagnostic, and prognostic applications and for guiding prevention and treatment of acute VTE. Where the smart sensor determines a risk for VTE, then the decision support tool may initiate an intervening action.