Abstract: A method for real-time, interactive development and testing of workflows for patient care access and selection may include receiving, by a guided workflow builder user interface (UI) engine, user input including a selection of at least one user interface element, the selected user interface element representing a step in a workflow and associated with at least one state. The guided workflow builder UI engine generates a file including pseudocode providing at least one configuration instruction for configuring the workflow to include the step and transmits the generated file to a parser. The parser parses the generated file and converts the at least one configuration instruction into a state chart including at least one state machine associated with at least one instruction for providing functionality during execution of the workflow. The previewer user interface executes the state chart generated by the parser and displaying an output of executing the state chart.

Abstract: A method for filtered, real-time referral searches includes receiving, by an analysis engine, during a patient interaction between a patient and an operator, an identification of a clinical need. The analysis engine analyzes the identification of the clinical need and data associated with the patient to determine at least one patient requirement. The analysis engine identifies a plurality of medical providers as potential referrals for the patient. The analysis engine generates a question to ask the patient and modifies a user interface displayed to the operator, during the patient interaction, to include the generated question. The analysis engine receives input responsive to the generated question. The analysis engine accesses at least one state machine to filter the plurality of medical providers. The analysis engine modifies, during the patient interaction, the user interface, resulting in a display of an identification of each medical provider in the filtered set of medical providers.

Abstract: A generalized input/output application programming interface (API) may provide an interface to file related operations. As a result of using this API, users of the array-based programming language may be able to manipulate stored data as though the data were a virtual array loaded into memory. Users do not need to memorize a different API in order to access data which may be stored in different file or data formats. In addition, using this API simplifies the task of working with large data sets by giving users seamless access to the sections of data they want to operate on when the entire data is too large to be loaded into memory.

Abstract: A computing device-implemented method includes receiving a program, analyzing and transforming the program, determining an inner context and an outer context of the program based on the analysis of the program, and allocating one or more portions of the inner context of the program to two or more labs for parallel execution. The method also includes receiving one or more results associated with the parallel execution of the one or more portions from the two or more labs, and providing the one or more results to the outer context of the program.

Abstract: A computing device-implemented method includes receiving a program created by a technical computing environment, analyzing the program, generating multiple program portions based on the analysis of the program, dynamically allocating the multiple program portions to multiple software units of execution for parallel programming, receiving multiple results associated with the multiple program portions from the multiple software units of execution, and providing the multiple results or a single result to the program.

Abstract: A computing device-implemented method includes receiving a program, analyzing and transforming the program, determining an inner context and an outer context of the program based on the analysis of the program, and allocating one or more portions of the inner context of the program to two or more labs for parallel execution. The method also includes receiving one or more results associated with the parallel execution of the one or more portions from the two or more labs, and providing the one or more results to the outer context of the program.

Abstract: A device, for performing parallel processing, includes a processor to receive one or more portions of an inner context of a program created for a technical computing environment, and allocate one or more portions of the inner context of the program to two or more labs for parallel execution. The processor is also configured to receive one or more results associated with the parallel execution of the one or more portions from the two or more labs, and provide the one or more results to an outer context of the program.

Abstract: One or more computer-readable media store executable instructions that, when executed by processing logic, perform parallel processing. The media store one or more instructions for receiving one or more portions of an inner context of a program created for a technical computing environment, allocating one or more portions of the inner context of the program to two or more labs for parallel execution, receiving one or more results associated with the parallel execution of the one or more portions from the two or more labs, and providing the one or more results to an outer context of the program.

Abstract: A computing device-implemented method includes receiving a program, analyzing and transforming the program, determining an inner context and an outer context of the program based on the analysis of the program, and allocating one or more portions of the inner context of the program to two or more labs for parallel execution. The method also includes receiving one or more results associated with the parallel execution of the one or more portions from the two or more labs, and providing the one or more results to the outer context of the program.

Abstract: A computing system receives a program created by a technical computing environment, analyzes the program, generates multiple program portions based on the analysis of the program, dynamically allocates the multiple program portions to multiple software units of execution for parallel programming, receives multiple results associated with the multiple program portions from the multiple software units of execution, and provides the multiple results or a single result to the program.

Abstract: A computing device-implemented method includes receiving a program created by a technical computing environment, analyzing the program, generating multiple program portions based on the analysis of the program, dynamically allocating the multiple program portions to multiple software units of execution for parallel programming, receiving multiple results associated with the multiple program portions from the multiple software units of execution, and providing the multiple results or a single result to the program.

Abstract: A computing device-implemented method includes receiving a program created by a technical computing environment, analyzing the program, generating multiple program portions based on the analysis of the program, dynamically allocating the multiple program portions to multiple software units of execution for parallel programming, receiving multiple results associated with the multiple program portions from the multiple software units of execution, and providing the multiple results or a single result to the program.

Abstract: One or more computer-readable media store executable instructions that, when executed by processing logic, perform parallel processing. The media store one or more instructions for receiving one or more portions of an inner context of a program created for a technical computing environment, allocating one or more portions of the inner context of the program to two or more labs for parallel execution, receiving one or more results associated with the parallel execution of the one or more portions from the two or more labs, and providing the one or more results to an outer context of the program.

Abstract: A computing device-implemented method includes initiating a single programming language, and identifying, via the single programming language, one or more data distribution schemes for executing a program. The method also includes transforming, via the single programming language, the program into a parallel program with an optimum data distribution scheme selected from the one or more identified data distribution schemes, and allocating the parallel program to two or more labs for parallel execution. The method further includes receiving one or more results associated with the parallel execution of the parallel program from the two or more labs, and providing the one or more results to the program.

Abstract: A device for performing parallel processing includes a processor to initiate a single programming language, and identify, via the single programming language, one or more data distribution schemes for executing a program. The processor also transforms, via the single programming language, the program into a parallel program with an optimum data distribution scheme selected from the one or more identified data distribution schemes, and allocates the parallel program to two or more labs for parallel execution. The processor further receives one or more results associated with the parallel execution of the parallel program from the two or more labs, and provides the one or more results to the program.

Abstract: A computing device-implemented method includes receiving a program, analyzing and transforming the program, determining an inner context and an outer context of the program based on the analysis of the program, and allocating one or more portions of the inner context of the program to two or more labs for parallel execution. The method also includes receiving one or more results associated with the parallel execution of the one or more portions from the two or more labs, and providing the one or more results to the outer context of the program.

Abstract: One or more computer-readable media store executable instructions that, when executed by processing logic, perform parallel processing. The media store one or more instructions for initiating a single programming language, and identifying, via the single programming language, one or more data distribution schemes for executing a program. The media also store one or more instructions for transforming, via the single programming language, the program into a parallel program with an optimum data distribution scheme selected from the one or more identified data distribution schemes, and allocating the parallel program to two or more labs for parallel execution. The media further store one or more instructions for receiving one or more results associated with the parallel execution of the parallel program from the two or more labs, and providing the one or more results to the program.

Abstract: A device, for performing parallel processing, includes a processor to receive one or more portions of an inner context of a program created for a technical computing environment, and allocate one or more portions of the inner context of the program to two or more labs for parallel execution. The processor is also configured to receive one or more results associated with the parallel execution of the one or more portions from the two or more labs, and provide the one or more results to an outer context of the program.

Abstract: A computing system receives a program created by a technical computing environment, analyzes the program, generates multiple program portions based on the analysis of the program, dynamically allocates the multiple program portions to multiple software units of execution for parallel programming, receives multiple results associated with the multiple program portions from the multiple software units of execution, and provides the multiple results or a single result to the program.

Abstract: A computing device-implemented method includes receiving a program created by a technical computing environment, analyzing the program, generating multiple program portions based on the analysis of the program, dynamically allocating the multiple program portions to multiple software units of execution for parallel programming, receiving multiple results associated with the multiple program portions from the multiple software units of execution, and providing the multiple results or a single result to the program.