Medical Form Filling Using Retrieval-Augmented Context Matching
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Solution Overview
Problem
Existing language models struggle with efficiently filling structured data due to contextual information requirements that are not readily apparent from the document itself, making the process time-consuming and error-prone.
Innovation Solution
An automated system using retrieval augmented generation, combining optical character recognition (OCR) with large language models (LLM) to extract information from contextual documents and structured data, employing embedding and retrieval techniques to fill structured fields accurately.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If existing language models are used to fill structured data, then the process can be automated, but the accuracy and completeness deteriorate due to inability to comprehend contextual information
Solution Approach 1:
The patent introduces an intermediary retrieval system that acts as a bridge between the language model and the structured data filling task. The system retrieves relevant contextual information from external sources and provides it to the language model, enabling accurate form filling without sacrificing automation. This intermediary layer resolves the contradiction by enhancing the model's contextual understanding while maintaining automated operation.
2Measurement precision
If manual process is used to complete structured data, then accuracy can be maintained, but productivity deteriorates due to time-consuming nature
Solution Approach 1:
The patent replaces the manual mechanical process of form filling with an automated system that uses retrieval augmented generation. The system automatically retrieves relevant information, processes it through language models, and fills structured data without human intervention. This substitution maintains high accuracy while dramatically improving productivity by eliminating manual labor.
3Measurement precision
If contextual information is extensively searched to improve filling accuracy, then precision improves, but time consumption increases
Solution Approach 1:
The patent implements preliminary action by pre-processing and organizing contextual information into searchable formats before the actual form filling task. The system prepares retrieval indexes and structures data in advance, enabling rapid information access during form completion. This preliminary preparation reduces retrieval time while maintaining high precision in information matching.
Data Source
AI summary
Methods and systems for filling data include extracting text from a structured document and document instructions to identify a field within the structured document. Text is extracted from a contextual document to identify information relating to the field. Information is selected from the contextual document based on a comparison between the extracted text from the contextual document and the extracted text from the structured document and document instructions. The field within the structured document is filled using the selected information to create a filled document.