Clinical Protocol Document Generation With Indexed LLM Retrieval
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Solution Overview
Problem
The generation of clinical trial documents and data using large language models is time-consuming and costly, and there is a risk of inaccuracies due to hallucination from learning public open general data.
Innovation Solution
A system and method utilizing a service provision module, large language model, and document management module to generate documents and data based on clinical protocols, incorporating a conversion rule management unit, clinical protocol index unit, and assistant information generation to enhance accuracy and efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If large language model is used to generate clinical trial documents and data, then productivity is improved, but manufacturing precision deteriorates due to hallucination from learning public open general data
Solution Approach 1:
The patent introduces an intermediary retrieval system that acts as a mediator between the large language model and the clinical protocol data. The system retrieves relevant information from indexed clinical protocols before generating documents, ensuring the LLM works with accurate, protocol-specific data rather than relying solely on its trained general knowledge, thereby reducing hallucination while maintaining generation efficiency
Solution Approach 2:
The system performs preliminary indexing and retrieval of clinical protocol data before the document generation process. By pre-processing and organizing the protocol information into searchable structures, the system ensures accurate information is readily available to guide the LLM's document generation, preventing accuracy degradation while preserving productivity benefits
2Manufacturing precision
If various documents and data are generated manually based on clinical protocol, then manufacturing precision is maintained, but productivity deteriorates due to enormous amount of work
Solution Approach 1:
The patent merges the advantages of manual precision with automated efficiency by combining the large language model's document generation capability with a retrieval system that provides protocol-specific guidance. This hybrid approach allows automated generation to maintain the accuracy of manual processes while achieving the productivity benefits of automation
Solution Approach 2:
The system implements feedback mechanisms where the retrieval component continuously provides relevant protocol information to the LLM during document generation. This feedback loop ensures the generated documents remain aligned with protocol requirements, maintaining precision while enabling automated high-volume document production
Data Source
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AI summary
The present invention relates to a system for generating related documents and data on the basis of a clinical protocol using a large language model, and the system comprises: a service provision module for receiving a clinical protocol from at least one user terminal, generating documents and/or data related to the clinical protocol, and providing the documents and/or data to the at least one user terminal; and a large language model for receiving at least one prompt and information related to the clinical protocol indexed by the service provision module from the service provision module, and providing an output thereof to the service provision module, wherein the service provision module includes: a conversion rule management unit for providing a conversion rule generation function including the at least one prompt to the user terminal; and a conversion execution unit for providing the conversion rule and the clinical protocol to the large language model, and providing documents and/or data output from the large language model to the at least one user terminal in a final output form.