Electronic Document Preview Generation via Template Extraction
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Solution Overview
Problem
The medical services industry faces challenges in quickly identifying relevant electronic documents amidst vast and complex data repositories, making it difficult for practitioners to locate necessary information across different health information systems.
Innovation Solution
A method and apparatus for generating previews of electronic documents by processing a list of documents to extract pertinent preview data, using identified templates based on document attributes and usage parameters, allowing for efficient display of relevant information to users.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If entire electronic documents are rendered for display, then complete information is provided to users, but processing resources and time are excessively consumed
Solution Approach 1:
The patent extracts only the essential preview data from electronic documents using template-based identification. The system identifies and extracts specific data elements (such as patient name, document type, key findings) from the full document without rendering the entire document, thereby providing sufficient information for users to determine document relevance while significantly reducing processing time and resource consumption.
Solution Approach 2:
The patent segments the document processing into two distinct stages: (1) generating a preview with essential information using template-based extraction, and (2) providing full document access only when needed. This segmentation allows users to quickly assess document relevance through previews without the system needing to process and render complete documents for every viewing request.
2Productivity
If templates are used to extract preview data, then processing efficiency is improved, but adaptability to different document formats may be reduced
Solution Approach 1:
The patent implements universal templates that can adapt to multiple document formats and types. The template system is designed to identify and extract relevant data elements across different electronic document formats (such as PDF, Word, plain text) and document types (such as medical records, lab results, discharge summaries). This universality allows the system to maintain high processing efficiency while remaining adaptable to various document formats through a single flexible template framework.
Data Source
AI summary
Embodiments provided herein provide for customized previews of electronic documents. A template for a particular electronic document may be identified based on document attributes and/or usage parameters. The identified template may define pertinent data to be extracted from structured documents. Portions of documents, including unstructured documents can be provided as a preview such as by rendering an area of the document such as one defined in the template by coordinates or pixels. In this regard, individual users or user groups may configure what data is displayed in a document preview such as by selecting fields and/or by specifying locations of interest within the document. Users can view listings of documents and their respective previews such that the desired document may be identified without rendering complete documents.