Graph-Based Medical Report Generation System
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Solution Overview
Problem
Current technologies face challenges in generating comprehensive and accurate medical documents, such as interpretation reports, due to the increasing amount of information from medical images, often resulting in omitted or redundant sentences when dealing with complex and large amounts of data.
Innovation Solution
An information processing apparatus and method that generates a graph structure from element information related to medical diagnosis, connecting nodes representing various pieces of information to create coherent sentences, using a trained model to process the graph structure and produce well-structured reports.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If traditional sentence generation methods are used to create medical documents from medical image analysis results, then the process can handle simple cases, but information is omitted or sentences become redundant when dealing with large amounts of analysis results
Solution Approach 1:
The patent segments the sentence generation process into multiple specialized modules: a graph structure generation unit that organizes element information, a sentence generation unit that creates sentences from the graph structure, and a redundancy removal unit that eliminates duplicate sentences. This segmentation allows each module to focus on a specific task, improving information completeness while managing system complexity through modular design.
Solution Approach 2:
The patent introduces a graph structure as an intermediary data representation between the input element information and the output sentences. The graph structure generation unit transforms unstructured element information into a structured graph format that captures relationships between medical findings, which then serves as input for the sentence generation unit. This intermediary structure enables more accurate and complete sentence generation.
2Quantity of substance
If the amount of medical image analysis results increases, then more comprehensive diagnosis information is available, but the amount of sentences in medical documents increases leading to redundancy and omission
Solution Approach 1:
The patent performs preliminary organization of element information into a graph structure before sentence generation. The graph structure generation unit pre-processes the input data by establishing relationships between medical findings, which facilitates more efficient and accurate sentence generation in subsequent steps, thereby improving overall productivity despite increased information volume.
Solution Approach 2:
The patent implements a feedback mechanism through the redundancy removal unit, which analyzes generated sentences and removes duplicate or redundant information. This feedback loop ensures that the final medical document maintains high quality and completeness without unnecessary repetition, efficiently handling large amounts of diagnosis information.
3Reliability
If multiple pieces of element information are generated from medical images, then diagnostic accuracy is improved, but generating coherent sentences from this information becomes more difficult
Solution Approach 1:
The patent segments the complex task of sentence generation from multiple element information pieces into manageable steps: first organizing the information into a graph structure that captures relationships, then generating sentences from this structured representation. This segmentation makes the process more manageable and coherent despite the large number of input elements.
Solution Approach 2:
The graph structure serves as an intermediary that organizes multiple piece of element information in a coherent manner before sentence generation. By representing relationships between medical findings in the graph structure, the system maintains diagnostic accuracy while simplifying the subsequent sentence generation process.
Data Source
AI summary
An information processing apparatus including at least one processor, wherein the processor is configured to: generate a graph structure represented by a node indicating each of a plurality of pieces of element information used for medical diagnosis and an edge connecting the nodes of the related pieces of element information; and generate a sentence related to the medical diagnosis based on the graph structure.