An automated method for search includes: receiving search characters and a viewport location on a displayed geographic area corresponding to an area of interest; simultaneously searching a first entry source and a second entry source to obtain corresponding first suggested entries and second suggested entries, where the first suggested entries correspond to geographic locations that are closer to the viewport location; ranking the first suggested entries according to first rules of relevancy, and generating first ranked suggested entries; ranking the second suggested entries according to second rules of relevancy, and generating second ranked suggested entries; combining the first and second ranked suggested entries into a combined set of suggested entries, and ranking the combined set of suggested entries according to combined rules of relevancy, and generating combined ranked suggested entries; and transmitting the combined ranked suggested entries to a user for selection of a desired type ahead entry.

An automated method for search includes: receiving search characters and a viewport location on a displayed geographic area corresponding to an area of interest; simultaneously searching a first entry source and a second entry source to obtain corresponding first suggested entries and second suggested entries, where the first suggested entries correspond to geographic locations that are closer to the viewport location; ranking the first suggested entries according to first rules of relevancy, and generating first ranked suggested entries; ranking the second suggested entries according to second rules of relevancy, and generating second ranked suggested entries; combining the first and second ranked suggested entries into a combined set of suggested entries, and ranking the combined set of suggested entries according to combined rules of relevancy, and generating combined ranked suggested entries; and transmitting the combined ranked suggested entries to a user for selection of a desired type ahead entry.

A method, computer program product, and computing system for proactive encounter scanning is executed on a computing device and includes obtaining encounter information of a patient encounter. The encounter information is proactively processed to determine if the encounter information is indicative of one or more medical conditions and to generate one or more result set. The one or more result sets are provided to the user.

A method, computer program product, and computing system for proactive encounter scanning is executed on a computing device and includes obtaining encounter information of a patient encounter. The encounter information is proactively processed to determine if the encounter information is indicative of one or more medical conditions and to generate one or more result set. The one or more result sets are provided to the user.

Users of a database management engine may generate fillable digital documents by mapping interface elements onto form documents. When a user maps interface elements onto a form document, the user may accidentally overlap two or more interface elements. To rectify this, the database management engine may modify the position of one of interface elements based on a set of positioning rules. In addition, the database management engine may identify and suggest mappings to users based on similar documents that have been previously mapped. The database management engine identifies similar documents using information about the document, the user, and the mapping itself. The mapping associated with the most similar document may be provided to the user as a suggested mapping. The database management engine converts the form document and finalized mapping into a fillable digital document. The fillable digital document is sent to recipients, who complete the fillable digital document.

Users of a database management engine may generate fillable digital documents by mapping interface elements onto form documents. When a user maps interface elements onto a form document, the user may accidentally overlap two or more interface elements. To rectify this, the database management engine may modify the position of one of interface elements based on a set of positioning rules. In addition, the database management engine may identify and suggest mappings to users based on similar documents that have been previously mapped. The database management engine identifies similar documents using information about the document, the user, and the mapping itself. The mapping associated with the most similar document may be provided to the user as a suggested mapping. The database management engine converts the form document and finalized mapping into a fillable digital document. The fillable digital document is sent to recipients, who complete the fillable digital document.

Described are methods, systems and computer readable media for dynamic updating of query result displays.

Described are methods, systems and computer readable media for dynamic updating of query result displays.

Structured documents are processed using convolutional neural networks. For example, the processing can include receiving a rendered form of a structured document; mapping a grid of cells to the rendered form; assigning a respective numeric embedding to each cell in the grid, comprising, for each cell: identifying content in the structured document that corresponds to a portion of the rendered form that is mapped to the cell, mapping the identified content to a numeric embedding for the identified content, and assigning the numeric embedding for the identified content to the cell; generating a matrix representation of the structured document from the numeric embeddings assigned to the cells of the grids; and generating neural network features of the structured document by processing the matrix representation of the structured document through a subnetwork comprising one or more convolutional neural network layers.

Structured documents are processed using convolutional neural networks. For example, the processing can include receiving a rendered form of a structured document; mapping a grid of cells to the rendered form; assigning a respective numeric embedding to each cell in the grid, comprising, for each cell: identifying content in the structured document that corresponds to a portion of the rendered form that is mapped to the cell, mapping the identified content to a numeric embedding for the identified content, and assigning the numeric embedding for the identified content to the cell; generating a matrix representation of the structured document from the numeric embeddings assigned to the cells of the grids; and generating neural network features of the structured document by processing the matrix representation of the structured document through a subnetwork comprising one or more convolutional neural network layers.