Abstract: A system and method for developing a rule-based named entity extraction system is provided. The method includes analyzing requirements of business users. The method further includes designing the rule-based named entity extraction system based on the requirement analysis. Further, the method includes implementing the design of rule-based named entity extraction system using one or more GUI-based tools. Thereafter, regression testing of the rule-based named entity extraction system is conducted. Finally, rule-based named entity extraction system is deployed.

Abstract: A system and method for modeling a region segmented image is described. Aspects of the present invention may include the generation of a computer model that models the region segmented image, the computer model comprising one or more nodes, wherein each node in the one or more nodes represents an arbitrarily shaped region present in the region segmented image, and each of the arbitrarily shaped regions comprises an image segment wherein the image segment is an indivisible partition in the region segmented image. The model may additionally comprise one or more logical nodes, wherein each logical node represents an image region formed by the union of two or more arbitrarily shaped image regions in the region segmented image that exhibit at least one type of spatial relationship and a hierarchical graph representation of the region segmented image. Types of spatial relationships may include hierarchical, adjacent and cohesive spatial relationships.

Abstract: A system and method for modeling a region segmented image is described. Aspects of the present invention may include the generation of a computer model that models the region segmented image, the computer model comprising one or more nodes, wherein each node in the one or more nodes represents an arbitrarily shaped region present in the region segmented image, and each of the arbitrarily shaped regions comprises an image segment wherein the image segment is an indivisible partition in the region segmented image. The model may additionally comprise one or more logical nodes, wherein each logical node represents an image region formed by the union of two or more arbitrarily shaped image regions in the region segmented image that exhibit at least one type of spatial relationship and a hierarchical graph representation of the region segmented image. Types of spatial relationships may include hierarchical, adjacent and cohesive spatial relationships.

Abstract: The invention provides a method and clinical data mining system for enabling a user to derive knowledge from data corresponding to a plurality of electronic health records stored in a repository. One or more data elements are provided as an input. The data elements may include textual reports, images, and one or more criteria specified by the user. Information is extracted from one or more images associated with one or more electronic health records stored in the repository, based on the data elements. Further, information is extracted from one or more textual reports and structured data associated with the one or more electronic health records. Thereafter, one or more reports are generated based on the extracted information to enable the user to analyze the information. Subsequently, the user may derive knowledge from the data based on the analysis.

Abstract: A system and method for developing a rule-based named entity extraction system is provided. The method includes analyzing requirements of business users. The method further includes designing the rule-based named entity extraction system based on the requirement analysis. Further, the method includes implementing the design of rule-based named entity extraction system using one or more GUI-based tools. Thereafter, regression testing of the rule-based named entity extraction system is conducted. Finally, rule-based named entity extraction system is deployed.