Abstract: The present disclosure provides systems and methods supporting dynamic migration of jobs (e.g., workloads, containers, service requests, etc.) between execution environments. The disclosed systems and methods may utilize monitoring techniques to determine when a migration should occur and/or forecasting techniques to predict optimal times when a migration should occur. Upon determining a migration should occur, a target execution environment for a job may be identified and a migration process may be initiated. In some aspects, the migration may be performed partway through processing of the job and the migration may resume processing the job after the migration is completed in a manner that enables the processing to resume at the point where processing stopped prior to the migration.

Abstract: Systems and methods supporting discovery and quantification of vulnerabilities in software code are disclosed. The systems and methods provide functionality for using software code analysis and other types of tools to analyze the software code and determine whether it can be trusted. The software code tools may be able to discover various hidden issues in the software code and the outputs of such tools may be normalized to quantify the risk associated with vulnerabilities identified by the different tools. A labeling strategy is provided to label the software code to enable users to identify the best software among various available software options based on the label(s) and a set of criteria.

Abstract: A plurality of events are extracted from a plurality of electronic health records associated with a first patient. The extracted plurality of events are analyzed to identify a plurality of stimulus events and a plurality of response events. An association between a first stimulus event and a first response event is determined. A stimulus-response (SR) variable is generated for the first patient based at least in part on the determined association, and the generated SR variable is integrated into one or more predictive cognitive models.

Abstract: A study design guide method, system, and computer program product, include specifying a search parameter, analyzing a collection of unstructured documents using the search parameter, creating a list of informative terms and informative phrases related to design of a study cohort, and creating a visualization reflecting a level of importance, a frequency, and a relevancy of the informative terms and the informative phrases in relation to each other for a study design using the study cohort.

Abstract: A study design guide method, system, and computer program product, include specifying a search parameter, analyzing a collection of unstructured documents using the search parameter, creating a list of informative terms and informative phrases related to design of a study cohort, and creating a visualization reflecting a level of importance, a frequency, and a relevancy of the informative terms and the informative phrases in relation to each other for a study design using the study cohort.

Abstract: A plurality of events are extracted from a plurality of electronic health records associated with a first patient. The extracted plurality of events are analyzed to identify a plurality of stimulus events and a plurality of response events. An association between a first stimulus event and a first response event is determined. A stimulus-response (SR) variable is generated for the first patient based at least in part on the determined association, and the generated SR variable is integrated into one or more predictive cognitive models.

Abstract: A mechanism is provided in a data processing system comprising a processor and a memory, the memory comprising instructions that are executed by the processor to specifically configure the processor to implement a cognitive analysis engine for evaluating completeness of electronic medical record data sources. The cognitive analysis engine executing in the data processing system analyzes a plurality of patient electronic medical records (EMRs) from one or more EMR sources to determine whether each EMR in the plurality of patient EMRs satisfies a plurality of tests. Each test determines whether the EMR includes a set of attributes or portions of EMR data. The cognitive analysis engine generates a set of patient EMRs for each test in the plurality of tests based on results of the analysis. Each set of patient EMRs includes EMRs in the plurality of patient EMRs that satisfy the corresponding test. The cognitive analysis engine generates a diagram data structure, representing sets and their relationships.

Abstract: A mechanism is provided in a data processing system comprising a processor and a memory, the memory comprising instructions that are executed by the processor to specifically configure the processor to implement a cognitive analysis engine for evaluating completeness of electronic medical record data sources. The cognitive analysis engine executing in the data processing system analyzes a plurality of patient electronic medical records (EMRs) from one or more EMR sources to determine whether each EMR in the plurality of patient EMRs satisfies a plurality of tests. Each test determines whether the EMR includes a set of attributes or portions of EMR data. The cognitive analysis engine generates a set of patient EMRs for each test in the plurality of tests based on results of the analysis. Each set of patient EMRs includes EMRs in the plurality of patient EMRs that satisfy the corresponding test. The cognitive analysis engine generates a diagram data structure, representing sets and their relationships.