Abstract: A method is provided for a medical risk stratification system. The method may include establishing a medical risk process model indicative of interrelationships between a plurality of medical risks and a plurality of health parameters and obtaining a set of values corresponding to the plurality of health parameters. The method may also include calculating the values of the plurality of medical risks simultaneously based upon the set of values corresponding to the plurality of health parameters and the medical risk process model and presenting the values of the plurality of medical risks.

Abstract: An efficient organizer of companion guide rules is created by a validation application from the common set of rules among an industry's implementation guide and the rulebooks, such as companion guides of one or more entities, such as payers. The organizer of companion guide rules creates an inventory of all rules and a profile for each companion guide and stores each profile in metadata storage. Each profile contains pointers to code in the inventory for all the rules employed by the corresponding companion guide. After an EDI document reaches the validation application, a runtime checker engine checks metadata storage for a current rule set for the payer. A rule set is created the first time a profile is accessed during the validation process and whenever the profile is updated. The runtime checker engine attempts to validate the EDI document by comparing it to the current rule set for a payer's companion guide.

Abstract: The present invention relates to a system and method to facilitate data mining applications and automated evaluation of models for continuous variable data. In one aspect, a system is provided that facilitates decision tree learning. The system includes a learning component that generates non-standardized data that relates to a split in a decision tree and a scoring component that scores the split as if the non-standardized data at a subset of leaves of the decision tree had been shifted and/or scaled. A modification component can also be provided for a respective candidate split score on the decision tree, wherein the above data or data subset can be modified by shifting and/or scaling the data and a new score is computed on the modified data. Furthermore, an optimization component can be provided that analyzes the data and determines whether to treat the data as if it was: (1) shifted, (2) scaled, or (3) shifted and scaled.

Abstract: Methods, systems and apparatus for modeling a target system includes defining a constraint satisfaction problem (CSP) that characterizes the target system in terms of a set of variables, each having a respective input domain, and initial constraints applicable to the variables. The variables are partitioned into at least first and second sets. An abstract solution is found to the CSP, including a given assignment of the variables in the first set. A reduced domain of at least one of the variables in the second set is computed, so as to be compatible with the abstract solution. A redundant constraint on the abstract solution is determined responsively to the reduced domain. A concrete solution to the CSP is then found, using the abstract solution and the redundant constraint.

Abstract: The invention relates to an evolutionary optimization method. First, an initial population of individuals is set up and an original fitness function is applied. Then the offspring individuals having a high evaluated quality value as parents are selected. In a third step, the parents are reproduced to create a plurality of offspring individuals. The quality of the offspring individuals is evaluated selectively using an original fitness function or an approximate fitness function. Finally, the method returns to the selection step until a termination condition is met. The step of evaluating the quality of the offspring individuals includes grouping all offspring individuals in clusters, selecting for each cluster one or a plurality of offspring individuals, resulting in altogether selected offspring individuals, evaluating the selected offspring individuals by the original fitness function, and evaluating the remaining offspring individuals by means of the approximate fitness function.