Patent application number | Description | Published |
20080215411 | METHOD AND SYSTEM FOR PREDICTING RESOURCE REQUIREMENTS FOR SERVICE ENGAGEMENTS - A method and system for predicting resource requirements of a current service engagement by modeling records of past service engagements to create and classify templates of service resource usage. This is done by clustering past engagements into groups having similar time series requirements for service resources. A service resource template for the current service engagement is generated from a classified template by using characteristics of the current service engagement to select a group of which the current service engagement is a likely member. The corresponding template is then customized to fit the characteristics of the current service engagement. The invention may be implemented using Hidden Markov Models. An aspect of the invention is use of dynamic time warping to quantify dissimilarity between engagement sequences prior to fitting Hidden Markov Models. Another aspect of the invention is removal of outliers from the clustered groups. | 09-04-2008 |
20080219519 | Method and Apparatus for Rolling Enrollment for Signature Verification - Improved techniques are disclosed for adapting signature verification systems to natural signature variations. For example, a technique for adapting a signature verification system to variations in a signature of a user includes the following steps/operations. One or more signature samples are obtained from the user. The one or more obtained signature samples are submitted by the user as part of a regular authentication procedure associated with the signature verification system. A reference set of signature samples for the user is updated through selection of one or more signature samples from the obtained signature samples, such that the updated reference set is usable by the signature verification system for verifying subsequent signature samples attributed to the user. The selection of the one or more signature samples used to update the reference set is conditioned on a false rejection rate of the user when at least one obtained signature sample of the user is authenticated and on an identification check when no obtained signature sample is authenticated. | 09-11-2008 |
20080252499 | METHOD AND SYSTEM FOR THE COMPRESSION OF PROBABILITY TABLES - The present invention relates to a method, computer program product and system for the compression of a probability table and the reconstruction of one or more probability elements using the compressed data and method. After determining a probability table that is to be compressed, the probability table is compressed using a first probability table compression method, wherein the probability table compression method creates a first compressed probability table. The first compressed probability table contains a plurality of probability elements. Further, the probability table is compressed using a second probability table compression method, wherein the probability table compression method creates a second compressed probability table. The second compressed probability table containing a plurality of probability elements. A first probability element reconstructed using the first compressed probability table is thereafter merged with a second probability element reconstructed using the second compressed probability table in order to produce a merged probability element. | 10-16-2008 |
20090006173 | METHOD AND APPARATUS FOR IDENTIFYING AND USING HISTORICAL WORK PATTERNS TO BUILD/USE HIGH-PERFORMANCE PROJECT TEAMS SUBJECT TO CONSTRAINTS - A method for identifying and using historical work patterns to build high-performance project teams, in one aspect, may comprise identifying historical data associated with one or more past projects, determining from said historical data, one or more patterns in team member attributes that are correlated with at least one of an individual determined to be successful and a project determined to be successful, and generating one or more staffing plans based on said determined patterns. A system and program storage device for performing finctionalities of the method are also provided. | 01-01-2009 |
20090182771 | METHOD AND APPARATUS FOR INFORMATION BOOSTING IN RELATED BUT DISCONNECTED DATABASES - Method and apparatus for information boosting in related but disconnected databases, in one aspect, may comprise identifying disconnected data sources comprising data that are related or dependent on one another, determining one or more relationships and dependencies among the disconnected data, and refining the data sources based on one or more relationships and dependencies. | 07-16-2009 |
20100145961 | System and method for adaptive categorization for use with dynamic taxonomies - A system, method and computer program product provides a solution to a class of categorization problems using a semi-supervised clustering approach, the method employing performing a Soft Seeded k-means algorithm, which makes effective use of the side information provided by seeds with a wide range of confidence levels, even when they do not provide complete coverage of the pre-defined categories. The semi-supervised clustering is achieved through the introductions of a seed re-assignment penalty measure and model selection measure. | 06-10-2010 |
20110231336 | FORECASTING PRODUCT/SERVICE REALIZATION PROFILES - Past realization profiles can be used to predict future realization profiles using a similarity rubric that emphasizes relationships between the past realization profiles. That similarity rubric might involve techniques including manifold characterization of past realization profiles; predictive modeling; and/or matrix factorization. Realization profiles might be related to business projects and track features such as ongoing resource expenditure, revenues realized, or percentage project completion. Realization profiles might relate to other applications such as effectiveness of medical treatment. | 09-22-2011 |
20120030020 | COLLABORATIVE FILTERING ON SPARE DATASETS WITH MATRIX FACTORIZATIONS - A system, method and computer program product automatically present at least one product to at least one client for at least one possible purchase. The system applies a matrix factorization on a binary matrix X representing which clients purchased which products. The system optimizes zero-valued elements in the matrix X that correspond to unknown client-product affinities. The system constructs based on the optimization, a prediction matrix {circumflex over (X)} whose each element value represents a likelihood that a corresponding client purchases a corresponding product. The system identifies at least one client-product pair with the highest value in the matrix {circumflex over (X)}. The system recommends at least one product to at least one client according to the client-product pair with the highest value. | 02-02-2012 |
20120041277 | SYSTEM AND METHOD FOR PREDICTING NEAR-TERM PATIENT TRAJECTORIES - 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. | 02-16-2012 |
20120041772 | SYSTEM AND METHOD FOR PREDICTING LONG-TERM PATIENT OUTCOME - 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. | 02-16-2012 |
20120046992 | ENTERPRISE-TO-MARKET NETWORK ANALYSIS FOR SALES ENABLEMENT AND RELATIONSHIP BUILDING - There are provided a system, a method and a computer program product for increasing of productivity of sales force in a first entity. The system locates or constructs at least one enterprise social network in the first entity. The system constructs at least one market social network. The system creates at least one connection between the enterprise social network and the market social network. Sales representative in the first entity expands new sales operations and/or identify new markets via the connected social networks. | 02-23-2012 |
20120109683 | METHOD AND SYSTEM FOR OUTCOME BASED REFERRAL USING HEALTHCARE DATA OF PATIENT AND PHYSICIAN POPULATIONS - 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. | 05-03-2012 |
20120209620 | DETECTING UNEXPECTED HEALTHCARE UTILIZATION BY CONSTRUCTING CLINICAL MODELS OF DOMINANT UTILIZATION GROUPS - 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. | 08-16-2012 |
20130132308 | Enhanced DeepQA in a Medical Environment - A DeepQA engine is enhanced to provide a digital medical investigation tool which assists a medical professional in researching potential causes of a set of patient conditions, including clues, facts and factoids about the patient. The DeepQA engine provides one or more answers to a natural language question with confidence levels for each answer. If a confidence level falls below a threshold, the enhanced DeepQA engine performs a crowd sourcing operation to gather additional information from one or more domain experts. The domain expert responses are provided to the medical professional, and are learned by the enhanced DeepQA system to provide for better research of similar patient conditions in future queries. | 05-23-2013 |
20130144639 | ASSESSING PRACTITIONER VALUE IN MULTI-PRACTITIONER SETTINGS - 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. | 06-06-2013 |
20130231953 | METHOD, SYSTEM AND COMPUTER PROGRAM PRODUCT FOR AGGREGATING POPULATION DATA - 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. | 09-05-2013 |
20130282390 | COMBINING KNOWLEDGE AND DATA DRIVEN INSIGHTS FOR IDENTIFYING RISK FACTORS IN HEALTHCARE - 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. | 10-24-2013 |
20130282393 | COMBINING KNOWLEDGE AND DATA DRIVEN INSIGHTS FOR IDENTIFYING RISK FACTORS IN HEALTHCARE - 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. | 10-24-2013 |
20140058986 | Enhanced DeepQA in a Medical Environment - A DeepQA engine is enhanced to provide a digital medical investigation tool which assists a medical professional in researching potential causes of a set of patient conditions, including clues, facts and factoids about the patient. The DeepQA engine provides one or more answers to a natural language question with confidence levels for each answer. If a confidence level falls below a threshold, the enhanced DeepQA engine performs a crowd sourcing operation to gather additional information from one or more domain experts. The domain expert responses are provided to the medical professional, and are learned by the enhanced DeepQA system to provide for better research of similar patient conditions in future queries. | 02-27-2014 |
20140095184 | IDENTIFYING GROUP AND INDIVIDUAL-LEVEL RISK FACTORS VIA RISK-DRIVEN PATIENT STRATIFICATION - Systems and methods for individual risk factor identification include identifying common risk factors for one or more risk targets from population data. Individuals are stratified into clusters based upon the common risk factors. A discriminability of each of the common risk factors is determined, using a processor, for a target cluster using individual data of the target cluster to provide re-ranked common risk factors as individual risk factors for the target cluster, such that the discriminability is a measure of how a risk factor discriminates its cluster from other clusters. | 04-03-2014 |
20140095186 | IDENTIFYING GROUP AND INDIVIDUAL-LEVEL RISK FACTORS VIA RISK-DRIVEN PATIENT STRATIFICATION - Systems and methods for individual risk factor identification include identifying common risk factors for one or more risk targets from population data. Individuals are stratified into clusters based upon the common risk factors. A discriminability of each of the common risk factors is determined, using a processor, for a target cluster using individual data of the target cluster to provide re-ranked common risk factors as individual risk factors for the target cluster, such that the discriminability is a measure of how a risk factor discriminates its cluster from other clusters. | 04-03-2014 |
20140114671 | MAPPING A CARE PLAN TEMPLATE TO A CASE MODEL - A method of mapping a care plan template to a case model includes receiving a care plan template, extracting elements from the care plan template, wherein the elements correspond to a phase comprising at least one task and data attributes corresponding to the task, mapping the task of the care plan template to a task of the case model, mapping a precedence relationship of the task of the care plan template to preconditions of the task of the case model, mapping the data attributes of the care plan template to properties of the case model, wherein the properties are associated with the task of the case model, mapping the task of the care plan template to a role of the case model, and generating the case model including the mapped task, the mapped precedence relationship, the mapped data attributes, and the mapped role. | 04-24-2014 |
20140114673 | MAPPING A CARE PLAN TEMPLATE TO A CASE MODEL - A method of mapping a care plan template to a case model includes receiving a care plan template, extracting elements from the care plan template, wherein the elements correspond to a phase comprising at least one task and data attributes corresponding to the task, mapping the task of the care plan template to a task of the case model, mapping a precedence relationship of the task of the care plan template to preconditions of the task of the case model, mapping the data attributes of the care plan template to properties of the case model, wherein the properties are associated with the task of the case model, mapping the task of the care plan template to a role of the case model, and generating the case model including the mapped task, the mapped precedence relationship, the mapped data attributes, and the mapped role. | 04-24-2014 |
20140195260 | ASSESSING PRACTITIONER VALUE IN MULTI-PRACTITIONER SETTINGS - 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. | 07-10-2014 |
20140236544 | DYNAMIC IDENTIFICATION OF THE BIOMARKERS LEVERAGING THE DYNAMICS OF THE BIOMARKER - A system and method for providing a temporally dynamic model parameter include building a model parameter by minimizing a loss function based on patient measurements taken at a plurality of time points. Temporally related values of the model parameter are identified, using a processor, having a same type of patient measurement taken at different time points. At least one value of the model parameter and temporally related values of the at least one value are selected to provide a temporally dynamic model parameter. | 08-21-2014 |
20140236545 | DYNAMIC IDENTIFICATION OF THE BIOMARKERS LEVERAGING THE DYNAMICS OF THE BIOMARKER - A system and method for providing a temporally dynamic model parameter include building a model parameter by minimizing a loss function based on patient measurements taken at a plurality of time points. Temporally related values of the model parameter are identified, using a processor, having a same type of patient measurement taken at different time points. At least one value of the model parameter and temporally related values of the at least one value are selected to provide a temporally dynamic model parameter. | 08-21-2014 |
20140257045 | HIERARCHICAL EXPLORATION OF LONGITUDINAL MEDICAL EVENTS - Systems and methods for data analysis include determining medical events co-occurring within a time period from a patient record database. The medical events are grouped into sets of medical events such that a number of sets of medical events is minimized based upon medical event cardinality. Patterns from the sets of medical events are identified, using a processor, to provide relationships between the patterns and patient outcomes. | 09-11-2014 |
20140257847 | HIERARCHICAL EXPLORATION OF LONGITUDINAL MEDICAL EVENTS - Systems and methods for data analysis include determining medical events co-occurring within a time period from a patient record database. The medical events are grouped into sets of medical events such that a number of sets of medical events is minimized based upon medical event cardinality. Patterns from the sets of medical events are identified, using a processor, to provide relationships between the patterns and patient outcomes. | 09-11-2014 |
20140297240 | EXTRACTING CLINICAL CARE PATHWAYS CORRELATED WITH OUTCOMES - Systems and methods for data analysis include constructing patient traces as a set of medical events for each patient of a patient population, the patient population being segmented based on patient outcomes. Medical events in one or more of the patient traces are reduced to provide processed patient traces. The processed patient traces are clustered to identify a cluster of patient traces. A process model is mined, using a processor, representing an aggregation of treatment pathways in the patient traces from the cluster. Patterns from patient traces are identified that are discriminative of patient outcomes. At least one of the patterns is represented with respect to the process model to identify treatment pathways correlated with the patient outcomes. | 10-02-2014 |
20140297317 | EXTRACTING KEY ACTION PATTERNS FROM PATIENT EVENT DATA - Systems and methods for data analysis include determining a patient trace as a set of medical events for a patient. Medical events of the patient trace are grouped into subsets of medical events using a processor according to a temporal relationship between the medical events. Co-occurring events are identified from the subsets of medical events as event clusters. A plurality of medical events in one or more of the subsets of the patient trace is represented using the event clusters to condense the patient trace. | 10-02-2014 |
20140297323 | EXTRACTING KEY ACTION PATTERNS FROM PATIENT EVENT DATA - Systems and methods for data analysis include determining a patient trace as a set of medical events for a patient. Medical events of the patient trace are grouped into subsets of medical events using a processor according to a temporal relationship between the medical events. Co-occurring events are identified from the subsets of medical events as event clusters. A plurality of medical events in one or more of the subsets of the patient trace is represented using the event clusters to condense the patient trace. | 10-02-2014 |
20140297324 | EXTRACTING CLINICAL CARE PATHWAYS CORRELATED WITH OUTCOMES - Systems and methods for data analysis include constructing patient traces as a set of medical events for each patient of a patient population, the patient population being segmented based on patient outcomes. Medical events in one or more of the patient traces are reduced to provide processed patient traces. The processed patient traces are clustered to identify a cluster of patient traces. A process model is mined, using a processor, representing an aggregation of treatment pathways in the patient traces from the cluster. Patterns from patient traces are identified that are discriminative of patient outcomes. At least one of the patterns is represented with respect to the process model to identify treatment pathways correlated with the patient outcomes. | 10-02-2014 |
20150019232 | IDENTIFYING TARGET PATIENTS FOR NEW DRUGS BY MINING REAL-WORLD EVIDENCE - Systems and methods for patient identification include identifying a set of mature drugs similar to a target drug using a processor based on a drug similarity measure. A plurality of outcome models are constructed for each mature drug in the set based on real-world evidence, the plurality of outcome models representing a patient response to each mature drug. A patient response to the target drug is predicted based on the outcome models to identify patients for the target drug. | 01-15-2015 |
20150019239 | IDENTIFYING TARGET PATIENTS FOR NEW DRUGS BY MINING REAL-WORLD EVIDENCE - Systems and methods for patient identification include identifying a set of mature drugs similar to a target drug using a processor based on a drug similarity measure. A plurality of outcome models are constructed for each mature drug in the set based on real-world evidence, the plurality of outcome models representing a patient response to each mature drug. A patient response to the target drug is predicted based on the outcome models to identify patients for the target drug. | 01-15-2015 |