Electronic Document Retrieval via Physiological Image Segmentation
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Solution Overview
Problem
Physicians face inefficiencies in searching for medical documents related to specific clinical conditions due to the vast amount of data and the need for accurate keyword-based searches, which can be time-consuming and frustrating, especially when dealing with complex spellings.
Innovation Solution
A method and system for filtering electronic documents based on graphical representation, where a human physiological structure is segmented into portions associated with metadata, allowing users to select and retrieve relevant documents without needing the correct spelling, using a grid structure and metadata for query generation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If keyword-based search is used to find medical documents, then search precision can be improved, but search time and operational complexity increase significantly
Solution Approach 1:
The patent introduces an intermediary mapping system between colloquial patient symptoms and standardized medical keywords. This intermediary layer automatically translates user-friendly symptom descriptions into precise medical terminology, maintaining search accuracy while eliminating the time-consuming manual keyword lookup process. The mapping table acts as a mediator that bridges the gap between layman terms and medical jargon.
Solution Approach 2:
The system performs preliminary organization of medical documents by pre-tagging them with both standardized keywords and associated patient-friendly symptoms. This preliminary action creates a dual-indexed structure that allows users to search using simple symptom terms while the system has already prepared the precise keyword mappings, significantly reducing search time without sacrificing precision.
2Reliability
If manual reading of EHRs is performed to find clinical conditions, then comprehensive review is achieved, but productivity and efficiency decrease
Solution Approach 1:
The patent replaces the manual mechanical process of reading and analyzing each EHR document with an automated computational system. The system uses algorithmic matching between patient symptoms and medical document content, substituting human manual review with automated text processing and pattern recognition, thereby maintaining comprehensive review capability while dramatically improving productivity.
Solution Approach 2:
The system enables self-service searching where the automated system independently performs the comprehensive review function that previously required manual physician intervention. The computational system autonomously scans, analyzes, and retrieves relevant EHRs based on symptom matching, freeing physicians from this repetitive task while ensuring thorough review through systematic automated processing.
3Measurement precision
If accurate spelling of clinical conditions is required for search, then search precision is maintained, but ease of operation deteriorates
Solution Approach 1:
The patent inverts the traditional search approach by allowing users to search with simplified symptom terms instead of requiring precise medical keywords. Instead of the system adapting to user input precision, the system proactively maps imprecise user input to precise medical terminology, reversing the burden from user to system and dramatically improving ease of operation while maintaining search precision.
Solution Approach 2:
The system changes the parameter of search input from requiring precise medical terminology to accepting colloquial symptom descriptions. By transforming the input parameter requirements and using automated mapping to maintain precision, the system makes the search operation much more accessible to users without medical training while still achieving accurate document retrieval.
Data Source
AI summary
A method and a system for processing electronic documents are provided. The method includes displaying a first image. The first image includes one or more portions. The one or more portions are associated with metadata. A first portion of the one or more portions of the first image is selected. Upon selection of the first portion, at least one subsequent image is displayed based on a first selection. The subsequent images also include one or more portions associated with metadata. One or more subsequent portions of the at least one subsequent image is selected. Upon selecting the portions of the first image and the subsequent image, one or more electronic documents corresponding to the selections are retrieved.