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: Systems, methods and computer-readable media are provided for facilitating patient health care by providing discovery, validation, and quality assurance of nomenclatural linkages between pairs of terms or combinations of terms in databases extant on multiple different health information systems that do not share a set of unified codesets, nomenclatures, or ontologies, or that may in part rely upon unstructured free-text narrative content instead of codes or standardized tags. Embodiments discover semantic structures existing naturally in documents and records, including relationships of synonymy and polysemy between terms arising from disparate processes, and maintained by different information systems. In some embodiments, this process is facilitated by applying Latent Semantic Analysis in concert with decision-tree induction and similarity metrics.

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. Embodiments of the invention provide decision support services through new knowledge, including high-value itemsets having a plurality of codified clinical concepts from clinical information of a reference population and determining statistical measures of association between the high-value itemsets and codified clinical concepts in a target patient's electronic health records to determine additional clinical concepts that may be relevant for the patient. The high-value itemsets are discovered from the reference set of clinical information using data-mining approaches that include rare items and are linked to other clinical information to provide more contextually relevant information.

Abstract: A multi-variable statistical predictive leading-indicator approach is employed for identifying newborns at risk of clinically significant hyperbilirubinemia and for determining to administer interventions to at-risk newborns. In embodiments, a multi-variable logistic regression statistical model capable of calculating a probability of clinically significant hyperbilirubinemia is generated. Using an input data set for a newborn and the multi-variable logistic regression statistical model, a probability of clinically significant hyperbilirubinemia is determined for the newborn and presented to a clinician.

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 is communicated to the user's mobile device as they become available.

Abstract: Systems, methods and computer-readable media are provided for automatic identification of patients according to near-term risk of ventricular arrhythmias and sudden cardiac death (SCD). Embodiments of the invention are directed to event prediction, risk stratification, and optimization of the assessment, communication, and decision-making to prevent SCD, and in one embodiment take the form of a platform for wearable, mobile, unteathered monitoring devices with embedded decision support. Thus embodiments relate to automatically identifying persons at risk for arrhythmias and SCD through the use of noninvasive, portable, wearable electronic device and sensors equipped with signal-processing software and statistical predictive algorithms that calculate stability-theoretic measures derived from the digital electrocardiogram timeseries acquired by the device.

Abstract: Systems, methods and computer-readable media are provided for automatic identification of patients according to near-term risk of ventricular arrhythmias and sudden cardiac death (SCD). Embodiments of the invention are directed to event prediction, risk stratification, and optimization of the assessment, communication, and decision-making to prevent SCD, and in one embodiment take the form of a platform for wearable, mobile, unteathered monitoring devices with embedded decision support. Thus embodiments relate to automatically identifying persons at risk for arrhythmias and SCD through the use of noninvasive, portable, wearable electronic device and sensors equipped with signal-processing software and statistical predictive algorithms that calculate stability-theoretic measures derived from the digital electrocardiogram timeseries acquired by the device.

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: A multi-variable statistical predictive leading-indicator approach is employed for identifying newborns at risk of clinically significant hyperbilirubinemia and for determining to administer interventions to at-risk newborns. In embodiments, a multi-variable logistic regression statistical model capable of calculating a probability of clinically significant hyperbilirubinemia is generated. Using an input data set for a newborn and the multi-variable logistic regression statistical model, a probability of clinically significant hyperbilirubinemia is determined for the newborn and presented to a clinician.

Abstract: A predictive model forecasts a medical resource need by making use of empirical Bayes estimation methods to determine a Dynamic Bayes Network (DBN) model. Exemplary resource needs that may be forecast include nurses, ventilators, hospital rooms, etc. The DBN model is estimated from retrieved data that is related to the resource to be forecast. The DBN model is simplified and a predictive model is generated based on the simplified model. The predictive model runs to forecast the predicted need for the resource. Embodiments are directed toward a predictive model development system that instructs an operator as to the structure of the data so that a model may be tailored based on the understanding of the operator. Embodiments are directed toward a model running system that indexes available models and also employs powerful statistical analysis techniques on behalf of a user to generate a predictive model with little or no user involvement in low-level modeling details.

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 is communicated to the user's mobile device as they become available.

Abstract: Methods, systems, and computer storage media are provided for predicting a probability of acute deterioration for a specific patient. Various discrete measurements are taken regarding the patient's current health. Those measurements are used to determine a PPOD score, which is displayed for clinicians.

Abstract: Methods, systems, and computer storage media are provided for determining whether a patient suffers from one or both of a recent deterioration in left ventricular function and a recent deterioration in mitral valve function. Transbrachial impedance velocimetry data and arterial pressure waveform data is received from a particular patient at a plurality of timepoints. An extent of deterioration is determined using a copula analysis of the patient data, and a statistical norm is determined for the patient's left ventricular function and mitral valve function. A current data value is received from the patient, including current transbrachial impedance velocimetry data and arterial pressure waveform data. The current data value is compared to the patient's statistical norm to determine whether the patient suffers from a recent deterioration in left ventricular function and/or mitral valve function.

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: Systems, methods and computer-readable media are provided for facilitating patient health care by providing discovery, validation, and quality assurance of nomenclatural linkages between pairs of terms or combinations of terms in databases extant on multiple different health information systems that do not share a set of unified codesets, nomenclatures, or ontologies, or that may in part rely upon unstructured free-text narrative content instead of codes or standardized tags. Embodiments discover semantic structures existing naturally in documents and records, including relationships of synonymy and polysemy between terms arising from disparate processes, and maintained by different information systems. In some embodiments, this process is facilitated by applying Latent Semantic Analysis in concert with decision-tree induction and similarity metrics.

Abstract: Optimal assignment of clients to client-sets, resources to resource-sets, and client-sets to resource-sets in a server farm allows for periodic re-balancing of the load as client usership and concurrent-user activity fluctuate. Unique combinations of clients are generated as candidate client-sets, and historical load measurements for clients in each candidate client-set are summed. Summed loads for the candidate client-sets are compared against available resources of resource-sets. An objective function is employed to identify optimal assignment of clients to client-sets, resources to resource-sets, and client-sets to resource-sets.

Abstract: Systems, methods and computer-readable media are provided for automatic identification of patients according to near-term risk of ventricular arrhythmias and sudden cardiac death (SCD). Embodiments of the invention are directed to event prediction, risk stratification, and optimization of the assessment, communication, and decision-making to prevent SCD, and in one embodiment take the form of a platform for wearable, mobile, unteathered monitoring devices with embedded decision support. Thus embodiments relate to automatically identifying persons at risk for arrhythmias and SCD through the use of noninvasive, portable, wearable electronic device and sensors equipped with signal-processing software and statistical predictive algorithms that calculate stability-theoretic measures derived from the digital electrocardiogram timeseries acquired by the device.

Abstract: A multi-variable statistical predictive leading-indicator approach is employed for identifying newborns at risk of clinically significant hyperbilirubinemia and for determining to administer interventions to at-risk newborns. In embodiments, a multi-variable logistic regression statistical model capable of calculating a probability of clinically significant hyperbilirubinemia is generated. Using an input data set for a newborn and the multi-variable logistic regression statistical model, a probability of clinically significant hyperbilirubinemia is determined for the newborn and presented to a clinician.

Abstract: A system, methods, A system, methods and computer-readable media are provided for the automatic identification of patients according to near-term risk of sudden kinematic injury (falling). Embodiments of the invention are directed to event prediction, risk stratification, and optimization of the assessment, communication, and decision-making to prevent falling in humans, and in one embodiment take the form of a platform for wearable, mobile, unteathered monitoring devices with embedded decision support.

Abstract: Methods, systems, and computer storage media are provided for predicting a probability of acute deterioration for a specific patient. Various discrete measurements are taken regarding the patient's current health. Those measurements are used to determine a PPOD score, which is displayed for clinicians.