Abstract: Performing an operation comprising generating, by a computing system based on data received from a plurality of data sources, a data model describing a patient, wherein the data comprises medical history data of the patient and observation data received by the computing system during observation of at least one medical professional, generating, by the computing system and based on the model applied to the received data, a plurality of candidate diagnoses for the patient, executing, by the computing system, a plurality of simulations of a plurality of candidate treatments generated by the computing system based on the model, and identifying a first candidate treatment of the plurality of candidate treatments that reduces an uncertainty value of the data model below a threshold.

Abstract: A system provides an intervention for a user and comprises at least one processor. The system monitors behavior and context of a user to generate a behavior history. One or more models are utilized to determine an intervention for the user to induce a behavior modification, wherein the one or more models map interventions to user context and behavior and utilize the behavior history to determine an effective intervention for the user. The intervention is provided to the user and feedback is received in response to the intervention. The one or more models are updated based on the feedback. Embodiments of the present invention further include a method and computer program product for providing an intervention to a user in substantially the same manner described above.

Abstract: 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.

Abstract: Performing an operation comprising generating, by a computing system based on data received from a plurality of data sources, a data model describing a patient, wherein the data comprises medical history data of the patient and observation data received by the computing system during observation of at least one medical professional, generating, by the computing system and based on the model applied to the received data, a plurality of candidate diagnoses for the patient, executing, by the computing system, a plurality of simulations of a plurality of candidate treatments generated by the computing system based on the model, and identifying a first candidate treatment of the plurality of candidate treatments that reduces an uncertainty value of the data model below a threshold.

Abstract: Patient assistant systems are provided. In various embodiments, health data of a user is read from one or more data source. A cohort of the user is determined based on a primary diagnosis of the user. The health data of the user includes the primary diagnosis. A co-morbidity of the primary diagnosis within the cohort is determined. One or more predictor of the co-morbidity within the cohort is determined. Assistance information is provided to the user based on the one or more predictor. The assistance information includes the predictor and one or more recommendation to mitigate the co-morbidity.

Abstract: A system provides an intervention for a user and comprises at least one processor. The system monitors behavior and context of a user to generate a behavior history. One or more models are utilized to determine an intervention for the user to induce a behavior modification, wherein the one or more models map interventions to user context and behavior and utilize the behavior history to determine an effective intervention for the user. The intervention is provided to the user and feedback is received in response to the intervention. The one or more models are updated based on the feedback. Embodiments of the present invention further include a method and computer program product for providing an intervention to a user in substantially the same manner described above.

Abstract: Mechanisms are provided to implement secure distributed patient consent and patient information management that addresses the competing needs for efficient access to electronic medical records by authorized parties while maintaining protection of privacy of patient health related information and complying with governing regulations. The mechanisms of the illustrative embodiments implement a tamper-proof and immutable ledger storage system to manage patient consent information and distribution of patient information based on the patient consent information. The ledger storage system operates in conjunction with a master patient record index (MPRI) component to enable the exchange of patient information among health providers once consent has been granted by the patient.

Abstract: Mechanisms are provided for executing patient information transactions. The mechanism store, in a ledger storage system, for each patient, a history of patient consents associated with patient transactions in a healthcare network, comprising patient consent data structures associated with the patient information transferred between participants as part of the transaction. The mechanisms store a master patient record index (MPRI) for each of the patients. The MPRI stores record locators identifying locations of portions of patient information for the patient on different computing devices associated with different health providers. The mechanisms execute, by a transaction manager, a transaction to grant access to a portion of a patient's information based on consent information stored in the ledger storage system and record locators in the MPRI. The mechanisms update, by a ledger storage engine of the data processing system, the history of transactions based on the execution of the transaction.

Abstract: An application as a service provided in a secure environment. A sandbox in a user's computing environment may be created. An application may be downloaded to the user's computing environment to run within the sandbox. Data sources associated with the user's computing environment may be searched and connectivity established with data registry of the data sources based on data description received with the application. The application may be run within the sandbox using the established connectivity. Metering may be performed to monitor usage of the application at the user's computing environment.

Abstract: An application as a service provided in a secure environment. A sandbox in a user's computing environment may be created. An application may be downloaded to the user's computing environment to run within the sandbox. Data sources associated with the user's computing environment may be searched and connectivity established with data registry of the data sources based on data description received with the application. The application may be run within the sandbox using the established connectivity. Metering may be performed to monitor usage of the application at the user's computing environment.

Abstract: A system and method for a composite distance metric leveraging multiple expert judgments includes inputting a data distribution of multiple expert judgments stored on a computer readable storage medium. Base distance metrics are converted into neighborhoods for comparison, wherein each base distance metric represents an expert and each neighborhood represents an individual similarity measure of the expert. The neighborhoods are combined to leverage the local discriminalities of all base distance metrics by applying at least one iterative process to output a composite distance metric.

Abstract: An application as a service provided in a secure environment. A sandbox in a user's computing environment may be created. An application may be downloaded to the user's computing environment to run within the sandbox. Data sources associated with the user's computing environment may be searched and connectivity established with data registry of the data sources based on data description received with the application. The application may be run within the sandbox using the established connectivity. Metering may be performed to monitor usage of the application at the user's computing environment.

Abstract: An application as a service provided in a secure environment. A sandbox in a user's computing environment may be created. An application may be downloaded to the user's computing environment to run within the sandbox. Data sources associated with the user's computing environment may be searched and connectivity established with data registry of the data sources based on data description received with the application. The application may be run within the sandbox using the established connectivity. Metering may be performed to monitor usage of the application at the user's computing environment.

Abstract: A system and method for a composite distance metric leveraging multiple expert judgments includes inputting a data distribution of multiple expert judgments stored on a computer readable storage medium. Base distance metrics are converted into neighborhoods for comparison, wherein each base distance metric represents an expert and each neighborhood represents an individual similarity measure of the expert. The neighborhoods are combined to leverage the local discriminalities of all base distance metrics by applying at least one iterative process to output a composite distance metric.

Abstract: A system and method for a composite distance metric leveraging multiple expert judgments includes inputting a data distribution of multiple expert judgments stored on a computer readable storage medium. Base distance metrics are converted into neighborhoods for comparison, wherein each base distance metric represents an expert. The neighborhoods are combined to leverage the local discriminalities of all base distance metrics by applying at least one iterative process to output a composite distance metric.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: A system and method for processing data includes organizing medical information in a concept frame data structure, which is adapted to include medical measurements and related metadata. The medical information is analyzed to extract further information using information extractors and to store extracted medical information in the concept frame data structure. References are stored to appropriate visualization methods along with an associated concept in the concept frame data structure.