Abstract: Systems, apparatuses, and methods are described herein for generating structured data from unstructured data using natural language processing to generate a secure medical dashboard. The present invention is configured to identify at least one data input, wherein the at least one data input comprises unstructured data; apply at least one NLP pipeline to the at least one data input; parse the unstructured data to generate a parsed unstructured dataset; identify a medical relevance attribute; generate a structured document comprising the at least one term and associated medical relevance attribute; correlate the at least one term comprising the positive medical attribute to a medical entity title; generate a medical dashboard interface component comprising the at least one term comprising the positive medical attribute and the medical entity title; transmit the medical dashboard interface component to a user device; and generate a secure medical dashboard on the user device.

Abstract: The invention provides a comprehensive data transformation system, method and computer program product structured for transformation of data structures to maintain data attribute equivalency in diagnostic databases.

Abstract: The invention provides a comprehensive data transformation system, method and computer program product structured for transformation of data structures to maintain data attribute equivalency in diagnostic databases. In some embodiments, the present invention is configured to determine a first source data structure based on at least received user information. The source data structure is typically comprises a comprising a first coding type. In addition, the present invention is configured to determine one or more source attributes associated with the first source data structure. Moreover, the present invention is configured for transforming the first source data structure to a first target data structure of a second coding type such that one or more target attributes associated with the first target data structure are equivalent to the one or more source attributes.

Abstract: The invention provides a comprehensive system, method and computer program product for data structure clustering based on variation in data attribute performance. In general, the invention is configured to link a sub-set of data structures out of a global set of data structures based on identifying stimulus type attributes that are structured to produce a functional performance parameter of the associated data structure, particularly in the field of hospital data analysis. Typically, the invention is configured to receive a request for construction of a peer data cluster for a first functional performance parameter of the first entity data structure. The invention may then determine at least one second entity data structure of a plurality of entity data structures that is a peer entity data structure, and linking the first entity data structure and the second entity data structure to form the peer data cluster.

Abstract: The present invention relates to providing systems, methods, and apparatuses for using machine learning to categorize and select suggested source entities. In some embodiments, such a system may comprise receiving a resource file from a user; normalizing the at least one supplier entity name to generate at least one normalized supplier entity name; determining the at least one normalized supplier entity name matches an authenticated supplier entity name of an entity name master record; updating a source entity management database; receiving a user indication; applying the at least one pre-determined variable standard and the selected category to a source entity suggestion model to output at least one suggested source entity name that matches the pre-determined variable standard and the selected category; and generating a suggested source entity interface component to configure a graphical user interface of a user device associated with the user.

Abstract: The present invention relates to system, method and computer program product for customized processing temporal resources and constructing resource values. The system comprises a computer-executable platform comprising a resource value construction module that is structured to access a data storage module and determine a resource value offer of the resource. The system further comprises a Bayesian network connected to the computer-executable platform. Moreover, the system comprises a user interface connected to the Bayesian network, the user interface comprising: a selection module that is structured to receive a user section of an indication of resource; and a management module that allows the user to manage the information of the resources via the user interface.

Abstract: The invention provides a comprehensive system, method and computer program product for data structure clustering based on variation in data attribute performance. In general, the invention is configured to link a sub-set of data structures out of a global set of data structures based on identifying stimulus type attributes that are structured to produce a functional performance parameter of the associated data structure, particularly in the field of hospital data analysis. Typically, the invention is configured to receive a request for construction of a peer data cluster for a first functional performance parameter of the first entity data structure. The invention may then determine at least one second entity data structure of a plurality of entity data structures that is a peer entity data structure, and linking the first entity data structure and the second entity data structure to form the peer data cluster.

Abstract: The invention provides a comprehensive system, method and computer program product for data structure clustering based on variation in data attribute performance. In general, the invention is configured to link a sub-set of data structures out of a global set of data structures based on identifying stimulus type attributes that are structured to produce a functional performance parameter of the associated data structure, particularly in the field of hospital data analysis. Typically, the invention is configured to receive a request for construction of a peer data cluster for a first functional performance parameter of the first entity data structure. The invention may then determine at least one second entity data structure of a plurality of entity data structures that is a peer entity data structure, and linking the first entity data structure and the second entity data structure to form the peer data cluster.

Abstract: The invention provides a comprehensive system, method and computer program product for data structure clustering based on variation in data attribute performance. In general, the invention is configured to link a sub-set of data structures out of a global set of data structures based on identifying stimulus type attributes that are structured to produce a functional performance parameter of the associated data structure, particularly in the field of hospital data analysis. Typically, the invention is configured to receive a request for construction of a peer data cluster for a first functional performance parameter of the first entity data structure. The invention may then determine at least one second entity data structure of a plurality of entity data structures that is a peer entity data structure, and linking the first entity data structure and the second entity data structure to form the peer data cluster.

Abstract: The invention provides a comprehensive data transformation system, method and computer program product structured for transformation of data structures to maintain data attribute equivalency in diagnostic databases. In some embodiments, the present invention is configured to determine a first source data structure based on at least received user information. The source data structure is typically comprises a comprising a first coding type. In addition, the present invention is configured to determine one or more source attributes associated with the first source data structure. Moreover, the present invention is configured for transforming the first source data structure to a first target data structure of a second coding type such that one or more target attributes associated with the first target data structure are equivalent to the one or more source attributes.

Abstract: A method for comparing a hospital's existing supply expenses to another hospital's existing supply expenses is described. The method includes determining a number of patient cases (Ci) associated with each diagnosis related classification (DRCi) from a plurality of DRCis, receiving a supply mix index weight (SMIi) value for each DRCi from the plurality of DRCis, and determining, with a processor, a weighted supply mix index value for each of the plurality of DRCis based on the SMIi value for each DRCi and the Ci for the corresponding DRCi. The method also includes determining an overall HCP supply mix index (HCPSMI) for the hospital based on the sum of the weighted supply mix index value for each of the plurality of DRCis and the sum of Ci for each of the plurality of DRCis, and outputting the HCPSMI for the hospital. Other methods, systems, and machine-readable media are also described.