Abstract: A plurality of actual outcome data points, including actual outcomes for a plurality of episodes of a process, are obtained for the process. A practitioner-independent baseline outcome is also obtained for the process. For each given one of the actual outcome data points, the given one of the actual outcome data points is equated to the practitioner entity-independent baseline outcome multiplied by a plurality of unknown participating practitioner entity outcome indices for each of a plurality of participating practitioner entities. Each of the participating practitioner entity outcome indices is raised to an exponent including a corresponding one of a plurality of unknown participating practitioner entity type indices, to obtain a plurality of equations. The plurality of equations are solved to obtain estimated values of the unknown participating practitioner entity outcome indices and estimated values of the unknown participating practitioner entity type indices.

Abstract: A recommendation system and method includes extracting patient features for a current patient to generate representation of the current patient. The patient features for the current patient are compared to physician features of one or more physicians and patient-to-physician features of a group of patients from medically related records. Outcome measures associated with physicians are compared related to a current query. A future outcome for patient, physician pairs are predicted for the current patient based upon at least one predictive model constructed from the features and outcome measures to output.

Abstract: A system and method for a composite distance metric leveraging multiple expert judgments includes inputting a data distribution of multiple expert judgments stored on a computer readable storage medium. Base distance metrics are converted into neighborhoods for comparison, wherein each base distance metric represents an expert. The neighborhoods are combined to leverage the local discriminalities of all base distance metrics by applying at least one iterative process to output a composite distance metric.

Abstract: A plurality of actual outcome data points, including actual outcomes for a plurality of episodes of a process, are obtained for the process. A practitioner-independent baseline outcome is also obtained for the process. For each given one of the actual outcome data points, the given one of the actual outcome data points is equated to the practitioner entity-independent baseline outcome multiplied by a plurality of unknown participating practitioner entity outcome indices for each of a plurality of participating practitioner entities. Each of the participating practitioner entity outcome indices is raised to an exponent including a corresponding one of a plurality of unknown participating practitioner entity type indices, to obtain a plurality of equations. The plurality of equations are solved to obtain estimated values of the unknown participating practitioner entity outcome indices and estimated values of the unknown participating practitioner entity type indices.

Abstract: Methods and systems for event pattern mining are shown that include representing longitudinal event data in a measurable geometric space as a temporal event matrix representation (TEMR) using spatial temporal shapes, wherein event data is organized into hierarchical categories of event type and performing temporal event pattern mining with a processor by locating visual event patterns among the spatial temporal shapes of said TEMR using a constraint sparse coding framework.

Abstract: Systems and methods for risk factor identification include identifying a first set of risk factors from personal data. A second set of risk factors is identified from at least one of a user input and a knowledge source. The first set is combined with the second set, using a processor, by selecting a number of risk factors from the first set that augment the second set of risk factors to determine a combined list of risk factors that predict a condition of interest.

Abstract: Systems and methods for risk factor identification include identifying a first set of risk factors from personal data. A second set of risk factors is identified from at least one of a user input and a knowledge source. The first set is combined with the second set, using a processor, by selecting a number of risk factors from the first set that augment the second set of risk factors to determine a combined list of risk factors that predict a condition of interest.

Abstract: A system and method for a composite distance metric leveraging multiple expert judgments includes inputting a data distribution of multiple expert judgments stored on a computer readable storage medium. Base distance metrics are converted into neighborhoods for comparison, wherein each base distance metric represents an expert. The neighborhoods are combined to leverage the local discriminalities of all base distance metrics by applying at least one iterative process to output a composite distance metric.

Abstract: A system, method and program product for matching members of a population, e.g., patients, based on member similarities. Patients are mapped to a bipartite graph with patient nodes connected by weighted edges to clustered factor nodes, are clustered categorically. As a new patient query is received, a similarity measure for each other patient is generated for each cluster by comparing cluster edges. The cluster similarity measures are aggregated for each patient to provide a global closeness measure to every other patient. Based on the global closeness measure, a list of the closest patients is displayed and measurement feedback may be provided.

Abstract: A plurality of actual outcome data points, including actual outcomes for a plurality of episodes of a process, are obtained for the process. A practitioner-independent baseline outcome is also obtained for the process. For each given one of the actual outcome data points, the given one of the actual outcome data points is equated to the practitioner entity-independent baseline outcome multiplied by a plurality of unknown participating practitioner entity outcome indices for each of a plurality of participating practitioner entities. Each of the participating practitioner entity outcome indices is raised to an exponent including a corresponding one of a plurality of unknown participating practitioner entity type indices, to obtain a plurality of equations. The plurality of equations arc solved to obtain estimated values of the unknown participating practitioner entity outcome indices and estimated values of the unknown participating practitioner entity type indices.

Abstract: A system and method for identifying unexpected utilization profiles at a patient level includes determining one or more clusters that have a profile based on patient profiles and building a representative model for each cluster including demographic and clinical information. Using the model, demographic and clinical characteristics are determined which form expected utilization cluster. An expected utilization cluster for each patient, which is derived from the demographic features and the clinical characteristics, is compared against an actual utilization profile for that patient to determine whether the actual utilization profile is unexpected.

Abstract: Methods and systems for event pattern mining are shown that include representing longitudinal event data in a measurable geometric space as a temporal event matrix representation (TEMR) using spatial temporal shapes, wherein event data is organized into hierarchical categories of event type and performing temporal event pattern mining with a processor by locating visual event patterns among the spatial temporal shapes of said TEMR using a constraint sparse coding framework.

Abstract: A recommendation system and method includes extracting patient features for a current patient to generate representation of the current patient. The patient features for the current patient are compared to physician features of one or more physicians and patient-to-physician features of a group of patients from medically related records. Outcome measures associated with physicians are compared related to a current query. A future outcome for patient, physician pairs are predicted for the current patient based upon at least one predictive model constructed from the features and outcome measures to output.

Abstract: A system and method for a composite distance metric leveraging multiple expert judgments includes inputting a data distribution of multiple expert judgments stored on a computer readable storage medium. Base distance metrics are converted into neighborhoods for comparison, wherein each base distance metric represents an expert. The neighborhoods are combined to leverage the local discriminalities of all base distance metrics by applying at least one iterative process to output a composite distance metric.

Abstract: A system and method for predicting patient prognosis includes a similarity module configured in program storage media to provide a similarity function for a data source and compute similarity scores for pairs of patients. An alignment module is configured to align a query patient to a best anchor timestamp of a similar patient or patients so that a comparison between the query patient and at least one similar patient is provided. A prediction module is configured to predict a long-term outcome measure of the query patient based on data from the at least one similar patient.

Abstract: A system and method for predicting near term measurements of a patient includes a stream processor configured to summarize raw measurements from patients into signatures and construct optimal prediction models based on previously obtained signatures. A similar patient tracker is configured to monitor similar patient information for a query patient. The similar patient information is determined based on a similarity between the query patient and signatures of other patients. A model analyzer is configured to employ retrofitted optimal prediction models from similar patients to predict near term measurements of the query patient.

Abstract: The present invention is directed to a method and apparatus for assisting in rating and filtering multimedia content, such as images, videos and sound recordings. One embodiment comprises a computer implemented method for rating the objectionability of specified digital content that comprises one or more discrete content items, wherein the method includes the step of moving the specified content to one or more filtering stages in a succession of filtering stages. After the specified content is moved to a given one of the filtering stages, a rating procedure is carried out to determine whether a rating can be applied to one or more of the content items, and if so, a selected rating is applied to each of the one or more content items. The method further comprises moving content items of the specified content to the next stage in the succession after the given stage, when at least one content item of the specified content remains without rating, after the rating procedure at the given stage.

Abstract: A method and apparatus is disclosed that receives an input narrative in a particular media format, and produces therefrom a multimedia enriched version of the input narrative. In one embodiment, a method is provided for enriching an input narrative with multimedia content, wherein the method includes the step of selectively segmenting the input narrative to form queries pertaining to different portions or elements of the input narrative. The method further comprises retrieving multimedia artifacts from one or more multimedia repositories, wherein each retrieved multimedia artifact is associated with one of the queries, and selecting a subset of the retrieved multimedia artifacts, wherein the subset includes artifacts comprising different types of multimedia content. The input narrative is then combined with respective multimedia artifacts of the subset, in order to provide an enriched and enhanced narrative.

Abstract: A system and method for processing data includes organizing medical information in a concept frame data structure, which is adapted to include medical measurements and related metadata. The medical information is analyzed to extract further information using information extractors and to store extracted medical information in the concept frame data structure. References are stored to appropriate visualization methods along with an associated concept in the concept frame data structure.

Abstract: The present invention is directed to a method and apparatus for assisting in rating and filtering multimedia content, such as images, videos and sound recordings. One embodiment comprises a computer implemented method for rating the objectionability of specified digital content that comprises one or more discrete content items, wherein the method includes the step of moving the specified content to one or more filtering stages in a succession of filtering stages. After the specified content is moved to a given one of the filtering stages, a rating procedure is carried out to determine whether a rating can be applied to one or more of the content items, and if so, a selected rating is applied to each of the one or more content items. The method further comprises moving content items of the specified content to the next stage in the succession after the given stage, when at least one content item of the specified content remains without rating, after the rating procedure at the given stage.