Abstract: A computer based media, method and system for developing at least one context frame that summarizes a measure performance situation for one or more levels of one or more organizations, providing applications for managing the measure performance that adapt to the performance situation by using a context frame and a database that automatically captures and incorporates any changes in the measure performance situation.

Abstract: A computer based media, method and system for developing at least one context frame that summarizes a measure performance situation for one or more levels of one or more organizations, providing applications for managing the measure performance that adapt to the performance situation by using a context frame and a database that automatically captures and incorporates any changes in the measure performance situation.

Abstract: A computer based media, method and system for developing at least one context frame that summarizes a measure performance situation for one or more levels of one or more organizations, providing applications for managing the measure performance that adapt to the performance situation by using a context frame and a database that automatically captures and incorporates any changes in the measure performance situation.

Abstract: A computer based media, method and system for developing at least one context frame that summarizes a measure performance situation for one or more levels of one or more organizations, providing applications for managing the measure performance that adapt to the performance situation by using a context frame and a database that automatically captures and incorporates any chances in the measure performance situation.

Abstract: An automated computer program product and system for using artificial intelligence based cognitive learning methods to create a custom risk transfer program for one or more organizations on a continual basis. The elements of value, external factors and segments of value of the one or more organizations are analyzed and modeled using predictive models that are developed by learning from the data associated with each of the organizations. Scenarios of both normal and extreme situations are also developed by learning from the data. The scenarios are then used to drive simulations of the predictive models. The outputs from these simulations are then used to calculate a risk by element of value, external factor and segment of value for each organization. A custom risk transfer program that optimizes financial performance for each of the organizations given the quantified value and risk is then identified and presented.

Abstract: An automated method, non-transitory computer-readable storage device and system for developing predictive models including predictive causal models and using said models to develop a personalized context for use in advertising, configuring, offering, producing, and/or delivering offerings that are appropriate to the context of a specific individual, group or organization.

Abstract: An automated method, computer readable storage device and system for using artificial intelligence based cognitive learning methods to develop predictive models and then use said models to measure and manage risk for an organization on a continual basis. The elements of value, external factors and segments of value of the organization are analyzed and modeled using predictive models and causal models that are developed by learning from the data associated with said organization. Scenarios of both normal and extreme situations are also developed by learning from the data. The scenarios are then used to drive simulations of the predictive models. The output from these simulations are then used to calculate and display a matrix of risk.

Abstract: This disclosure comprises a system, non-transitory computer readable storage medium and method for delivering medications and/or medical treatments that are appropriate to the resilient context of an individual patient. The resilient context comprises a predictive model for each of one or more patient function measures and a predictive model of patient resilience where said models are all developed by learning from the data associated with the individual patient. The medical advice, medical diagnoses and/or medical treatments may be provided “as is” and/or they may be customized to match the specific resilient context of the individual patient.

Abstract: This disclosure comprises a system, computer program product and apparatus for delivering medications and/or medical treatments that are appropriate to the resilient context of an individual patient. The resilient context comprises a predictive model for each of one or more patient function measures and a predictive model of patient resilience where said models are all developed by learning from the data associated with the individual patient. The medical advice, medical diagnoses and/or medical treatments may be provided “as is” and/or they may be customized to match the specific resilient context of the individual patient.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer readable storage medium, for using transfer learning to train a predictive model. In one aspect, a system receives predictive model training data. The training data and one or more training methods are used to train multiple predictive models. Variables and a predictive model type are then selected from the trained predictive models. The selected variables are then transferred into the selected type of predictive model as long as they reduce an error measure.

Abstract: A system, method and computer program product for developing an entity context frame or situation summary before using said context frame/situation summary to develop an index, perform a context search and return prioritized results. The search results may comprise a plurality of health related data where said health related data comprises a plurality of microbiome data.

Abstract: An automated method, computer program product and system for using artificial intelligence based cognitive learning methods to identify, measure and manage risks for a commercial enterprise on a continual basis. The elements of value, external factors, components of value and categories of value of the enterprise are analyzed and modeled using predictive models that are developed by learning from the data associated with said enterprise. Scenarios of both normal and extreme situations are also developed by learning from the data. The scenarios are then used to drive simulations of the predictive models. The output from these simulations are then used to measure a plurality of risks and complete optimization analyzes that identify the optimal mix of risk reduction activities for the enterprise. The optimal mix of risk reduction activities is then presented to the user for optional editing, rejection or acceptance.

Abstract: An automated method, computer program product and system for using artificial intelligence based cognitive learning methods to enable the identification and optional implementation of trades for an organization security. The elements of value, components of value and categories of value of the organization are analyzed and modeled using predictive models that are developed by learning from the data associated with said organization. The output from these models is then used to calculate a market sentiment value that is used to determine the types of trades that will be recommended and optionally completed.

Abstract: A method of, computer program product and system for transforming data representative of an enterprise and its employees into a plurality of models that identify the tangible contribution of one or more elements of value and external factors to both a pension plan for enterprise employees and the enterprise. The models which are developed using automated learning support the management and/or optimization of both the pension plan and the enterprise.

Abstract: A computer program product for using artificial intelligence based cognitive learning methods to enable the identification and optional implementation of the optimal mode for purchasing items and managing elements of value for a business enterprise. The items, elements of value and components of value of the business enterprise are analyzed and modeled using predictive models that are developed by learning from the data associated with said business enterprise. The output from these models is then used to identify and optionally implement the optimal mode for purchasing items while considering risk. The output from these models is also used to identify the optimal model for managing the elements of value for the business enterprise.

Abstract: An automated method, computer program product and system for using artificial intelligence based cognitive learning methods to measure and manage value for an organization on a continual basis. The elements of value, external factors and segments of value of the organization are analyzed and modeled using predictive models that are developed by learning from the data associated with said organization. Scenarios of both normal and extreme situations are also developed by learning from the data. The scenarios are then used to drive simulations of the predictive models. The output from these simulations are then used to calculate a risk adjusted value for the elements of value, the items within each element of value, the external factors and the items within each external factor. The optimal mix of changes to the element of value items and external factor items is also identified and presented to the user.

Abstract: An apparatus, computer program product and system for using artificial intelligence based cognitive learning methods to measure, manage and report value, risk and return for a portfolio on a continual basis. The elements of value, external factors and segments of value of the portfolio are analyzed and modeled by item using predictive models that are developed by learning from the data associated with said portfolio. Scenarios of both normal and extreme situations are also developed. The scenarios are then used to drive simulations of the predictive models. The output from these simulations are then used to calculate risks and a risk adjusted value for the elements of value, the items within each element of value, the external factors and the items within each external factor. The optimal mix of changes to the portfolio at the item level are also identified and presented to the user.

Abstract: An automated method, computer program product and system for using artificial intelligence based cognitive learning methods to create a custom risk transfer program for one or more organizations on a continual basis. The elements of value, external factors and segments of value of the one or more organizations are analyzed and modeled using predictive models that are developed by learning from the data associated with each of the organizations. Scenarios of both normal and extreme situations are also developed by learning from the data. The scenarios are then used to drive simulations of the predictive models. The output from these simulations are then used to calculate a risk by element of value, external factor and segment of value for each organization. A custom risk transfer program that optimizes financial performance for each of the organizations given the quantified value and risk is then identified and presented.

Abstract: Methods, computer program products and systems for developing and implementing a Knowledge Based Search System for an entity. Entity related data are analyzed as required to develop an entity knowledge and one or more knowledge graphs. The knowledge graphs are used to support the retrieval of relevant search results.

Abstract: A computer program product, method and system for transforming data into predictive models. The transformation of data into predictive models comprises a multi stage learning process that uses a plurality of algorithms at each stage to select output for use in the next stage. The final predictive model is a linear or nonlinear predictive model. Analyses of the model and the variables associated with it can be used to produce graphs and other management reports.