Layered Image Analysis for Handwritten Medical Record Extraction
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Solution Overview
Problem
Traditional OCR methods are inaccurate and unreliable in recognizing and extracting handwritten notes and uncommon terms from electronic documents, particularly in patient health records and other documentation.
Innovation Solution
A layered processing and analysis approach using artificial intelligence and machine learning to identify and extract information from electronic images, including a first layer of context extraction, a second layer of imaging content extraction, and a third layer of JSON data parsing, followed by creating multi-layered images and searchable documents.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional OCR methods are used to recognize textual elements, then the processing speed is maintained at acceptable levels, but the accuracy and reliability of recognizing handwritten notes and uncommon terms deteriorates significantly
Solution Approach 1:
The patent divides the document analysis into distinct layers: first layer for textual content extraction, second layer for imaging content extraction, and third layer for JSON data parsing. This segmentation allows each layer to specialize in specific tasks, improving overall accuracy while managing complexity through modular processing
Solution Approach 2:
The patent introduces a layered processing approach that adds dimensional complexity to the traditional single-pass OCR. By processing text and imaging content in separate layers and then integrating them, the system achieves higher recognition accuracy for handwritten notes and uncommon terms without overwhelming computational complexity
2Measurement precision
If manual steps are used for identifying and reviewing documents, then the accuracy of information extraction is improved, but the processing time and productivity deteriorate
Solution Approach 1:
The system performs automated multi-layered processing that eliminates the need for manual review steps. The first layer extracts textual content, the second layer extracts imaging content, and the third layer parses JSON data automatically, achieving both high accuracy and speed without human intervention
Solution Approach 2:
The patent implements continuous processing where layers operate in sequence without interruption. The extraction and parsing operations flow continuously through the layered architecture, maintaining high productivity while ensuring accurate extraction of all document elements including handwritten notes and uncommon terms
3Adaptability or versatility
If a single-layer processing approach is used, then the device complexity is minimized, but the ability to capture all types of content (printed text, handwritten notes, imaging content) deteriorates
Solution Approach 1:
The patent segments the processing into three distinct layers: first layer for textual content, second layer for imaging content, and third layer for JSON data parsing. This segmentation enables the system to capture all content types accurately while managing complexity through specialized modular processing
Solution Approach 2:
The layered architecture provides universal processing capability that handles multiple content types (printed text, handwritten notes, imaging content) through a unified multi-functional system. Each layer contributes specific functionality that collectively enables comprehensive content capture across diverse document formats
Data Source
AI summary
A machine translation of a document is created via a compilation of services by mapping textual content from an image to create a plurality of mapped locations correspondent to at least one object from the image, populating each of the mapped locations with at least one character indicative of the object, each character sharing at least one similar attribute, adding to the image the populated mapped locations, and highlighting at least a portion of the textual content in accordance with the populated at least one character. A compilation of services is provided for identifying, extracting, and assessing electronic images by using a layered approach that reduces time and improves reviewing of medical records and other kinds of documentation.