Medical Document Generation From Images With Adaptive Sentence Length
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Solution Overview
Problem
Existing methods for generating medical sentences from medical images often result in sentences that are either too long, burdening the reader, or too short, lacking necessary information, thus increasing the workload on radiologists and clinicians.
Innovation Solution
A document creation support apparatus and method that adjusts the sentence amount to a prescribed level by selecting, deleting, or integrating properties in the sentences, using a learning model to generate medical sentences with appropriate information content.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If the sentence generated by the learning model is too long, then the information content is comprehensive, but the burden on the reader becomes large
Solution Approach 1:
The system dynamically adjusts the sentence length parameter based on the complexity and importance of the medical finding. For routine findings, shorter sentences are generated, while complex or critical findings trigger longer sentences with more detailed descriptions, thus optimizing the balance between information density and readability.
Solution Approach 2:
The medical sentence is segmented into multiple components: key finding statements, supporting details, and contextual information. The system selectively assembles these segments based on the specific medical scenario, allowing the sentence length to be precisely controlled to match the reader's information needs.
2Ease of operation
If the medical sentence is too short, then the reading burden is reduced, but the reader is worried whether the sentence includes necessary information
Solution Approach 1:
The system incorporates feedback mechanisms where the generated sentence is evaluated against the original medical image findings and property information. This feedback loop ensures that the sentence length and content are continuously adjusted to maintain information completeness while optimizing readability.
Solution Approach 2:
The system applies partial action by selectively including only the necessary property information (shape, density, position, size) relevant to each specific finding, rather than always providing complete detailed descriptions. This allows concise sentences for routine findings while expanding to comprehensive descriptions only when clinically necessary.
3Loss of information
If the sentence amount is increased, then the information completeness is improved, but the time required for reading and processing increases
Solution Approach 1:
The sentence generation system is dynamic rather than static, automatically adjusting the amount of information provided based on real-time analysis of the medical image properties and the clinical context. This dynamic adaptation ensures that processing time is optimized by providing detailed information only when and where it is clinically relevant.
Data Source
AI summary
A document creation support apparatus includes at least one processor, and the processor generates a sentence related to a property of at least one structure of interest included in an image. The processor determines whether or not a sentence amount of the sentence is a prescribed amount. The processor adjusts the sentence amount such that the sentence amount is the prescribed amount based on a result of the determination.