Abstract: Various embodiments are provided for providing intelligent policy coverage optimization in a computing environment by a processor. One or more policy coverage gaps in one or more operational rules defined by one or more rules, policies, or a combination thereof and associated with one or more non-compliant policy claims associated with the one or more policy coverage gaps may be identified. The one or more policy coverage gaps may be ranked according to one or more selected criteria.

Abstract: Matrix inversion systems and methods are implemented using an analog resistive processing unit (RPU) array for hardware accelerated computing. A request is received from an application to compute an inverse matrix of a given matrix, and a matrix inversion process is performed in response to the received request. The matrix inversion process includes storing a first estimated inverse matrix of the given matrix in an array RPU cells, performing a first iterative process on the first estimated inverse matrix stored in the array of RPU cells to converge the first estimated inverse matrix to a second estimated inverse matrix of the given matrix, and reading the second estimated inverse matrix from the array of RPU cells upon completion of the first iterative process. An inverse matrix is returned to the application, wherein the returned inverse matrix is based, at least in part, on the second estimated inverse matrix.

Abstract: A system and method for analyzing and explaining the temporal evolution of policies. The analysis of the temporal evolution of policies includes determining semantically related changes in the text of the corresponding policies over time and across the different versions of the (two or more) policy documents. An explanation of the temporal evolution of policies is provided consisting of human interpretable information relating each change to one or more events and/or contextual data. A next steps policy change is also suggested that includes a set of policy conditions based on potential future changes of similar policies and contextual data and event data. The suggestions are related to the policy relevant to the target cohort or individual. The system adapts machine learned models by receiving user feedback provided on an analysis of the correctness of the temporal evolution of policies, corresponding explanations and suggestions of the next actions.

Abstract: Embodiments of the present invention provide a computer system, a computer program product, and a method that comprises identifying claim data from a received data set associated with a user; analyzing the identified claim data based on a historical database of claim information associated with the user; retrieving expert information associated with the analysis of the identified claim data; extracting the identified claim data based on a comparison of the analysis of identified claim data and the retrieved expert information associated with the claim data by normalizing a range of features of the analyzed data; dynamically determining an overall risk score associated with the extracted claim data; and dynamically transmitting the extracted claim data to a different computing device associated with a different user.

Abstract: Systems, computer-implemented methods, and computer program products to facilitate contextual comparison of semantics in conditions of different policies are provided. According to an embodiment, a system can comprise a processor that executes computer executable components stored in memory. The computer executable components can comprise a comparison component that contextually compares semantics of conditions in policy data of different policies based on a feature of at least one entity. The computer executable components further comprise a contextualization component that employs a model to provide a contextual explanation of how a first condition in first policy data of a first policy is semantically different from a second condition in second policy data of a second policy based on the feature of the at least one entity.

Abstract: Techniques are described for extracting structured information from unstructured documents based on validation of the structured information as applied to a domain problem associated with the unstructured documents. In one embodiment, a computer program product for automated information extraction is provided. The computer program product comprising a computer readable storage medium having program executable by a processing component to cause the processing component to extract structured candidate interpretations of a rule from unstructured information that defines a plurality of rules intended to control operations of a system, and determine measures of validity of the structured candidate interpretations based on application of the candidate policy interpretations to historical operational data for the system that represents operations performed by the system.

Abstract: Embodiments for intelligent recommendation of useful medical actions to a user by a processor. One or more useful medical actions may be cognitively recommended with evidence in support thereof for impacting a health state of a user according to historical data collected from one or more data sources, one or more user profiles, a domain knowledge, feedback data, or a combination thereof. The one or more useful medical actions may be ranked according to a scoring criteria, the domain knowledge, the historical data, a set of rules, previously recommended medical actions, or a combination thereof.

Abstract: Embodiments for intelligent learning for explaining anomalies to a user by a processor. One or more anomalous records may be identified in a knowledge base. A list of ranked candidate explanations may be generated for the one or more anomalous records. An active learning dialog may be initiated with one or more users to increase accuracy of the knowledge base, a domain knowledge, and each of the ranked candidate explanations.

Abstract: Various embodiments are provided for providing intelligent policy coverage optimization in a computing environment by a processor. One or more policy coverage gaps in one or more operational rules defined by one or more rules, policies, or a combination thereof and associated with one or more non-compliant policy claims associated with the one or more policy coverage gaps may be identified. The one or more policy coverage gaps may be ranked according to one or more selected criteria.

Abstract: Systems, computer-implemented methods and/or computer program products that facilitate answering questions that involve mathematical computations are provided. In one embodiment, a computer-implemented method comprises: transforming, by a system operatively coupled to a processor, a natural language query into a first logical representation and extrinsic knowledge into a second logical representation relevant to the natural language query; merging, by the system, the first logical representation and the second logical representation into a third logical representation; and generating, by the system, answers for the natural language query based on processing of the third logical representation.

Abstract: Systems, computer-implemented methods and/or computer program products that facilitate answering questions that involve mathematical computations are provided. In one embodiment, a computer-implemented method comprises: transforming, by a system operatively coupled to a processor, a natural language query into a first logical representation and extrinsic knowledge into a second logical representation relevant to the natural language query; merging, by the system, the first logical representation and the second logical representation into a third logical representation; and generating, by the system, answers for the natural language query based on processing of the third logical representation.

Abstract: Various embodiments are provided for intelligent application of operational rules to operational data in a computing environment by a processor. One or more operational rules may be extracted and formalized from a knowledge graph, a domain knowledge, or a combination thereof describing one or more operational policies and conditions. The one or more operational rules may be applied to operational data to identify and filter non-compliant operational data.

Abstract: Embodiments for intelligent generation of customized questions or questionnaires by a processor. One or more customized questions or questionnaires may be generated according to a user profile, similar profiles of alternative users, one or more historical interactions with the alternative users, one or more goals defined by a domain experts, domain knowledge, historical questions or questionnaires, or a combination thereof using a machine learning operation.

Abstract: A method includes: mapping a boundary of a volume of flowing fluid; partitioning the volume by a computational mesh; finding a contaminant location at a first sensor that is disposed within the volume; obtaining a measured velocity of the flowing fluid within the volume; generating a reversed velocity vector field within the mesh, in response to the measured velocity; time stepping the contaminant location from the first sensor along the reversed velocity vector field until the contaminant location intersects the boundary of the volume; and finding a contaminant source at the intersection of the time stepped contaminant location with the boundary of the volume.

Abstract: Various embodiments are provided for correcting policy data in a computing environment by a processor. Incorrect data of one or more rules extracted from one or more segments of text data may be revised to maintain accuracy and correctness of the policy data source according to an active learning operation.

Abstract: Techniques are described for extracting structured information from unstructured documents based on validation of the structured information as applied to a domain problem associated with the unstructured documents. In one embodiment, a computer program product for automated information extraction is provided. The computer program product comprising a computer readable storage medium having program executable by a processing component to cause the processing component to extract structured candidate interpretations of a rule from unstructured information that defines a plurality of rules intended to control operations of a system, and determine measures of validity of the structured candidate interpretations based on application of the candidate policy interpretations to historical operational data for the system that represents operations performed by the system.

Abstract: Embodiments for intelligent learning for explaining anomalies to a user by a processor. One or more anomalous records may be identified in a knowledge base. A list of ranked candidate explanations may be generated for the one or more anomalous records. An active learning dialog may be initiated with one or more users to increase accuracy of the knowledge base, a domain knowledge, and each of the ranked candidate explanations.

Abstract: Techniques for automated auditing claims are presented. A policy processor component can determine conditions and constraints relating to claim validity, based on a result of an analysis of policy data of a set of policies associated with a service identity and relating to services and procedures, to facilitate generation of probabilistic logic data relating to the conditions and constraints relating to the claim validity. The policy processor component can encode the conditions and the constraints to generate the probabilistic logic data, and store the probabilistic logic data and information relating to the conditions and constraints in a knowledge database component. A claim management component can determine a validity status of a claim and a probability that the validity status is correct based on evaluation of the probabilistic logic data and claim data relating to the claim. The validity status can be valid or invalid.

Abstract: Input text containing a plurality of patient information can be annotated for annotations and extracted. One or more annotations are parsed for relevant contextual information. The one or more annotations are assigned a semantic type. The one or more annotations are visually isolated, personalized to a user profile job, and outputted. The one or more extracted annotations are subjected to natural language processing operations.

Abstract: Embodiments for intelligent recommendation of useful medical actions to a user by a processor. One or more useful medical actions may be cognitively recommended with evidence in support thereof for impacting a health state of a user according to historical data collected from one or more data sources, one or more user profiles, a domain knowledge, feedback data, or a combination thereof. The one or more useful medical actions may be ranked according to a scoring criteria, the domain knowledge, the historical data, a set of rules, previously recommended medical actions, or a combination thereof.