Research on optimization of osteoporosis disease database construction process based on local large model

Corresponding author: zhouyi, zhouyi@mail.sysu.edu.cn

DOI: 10.12201/bmr.202410.00002

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  Abstract: Objective Utilize local large models combined with local knowledge base to optimize the osteoporosis disease database construction process and reduce the risk of medical data leakage. Methods First, relevant clinical research literature and business data information are collected and a local knowledge base is built. Then, based on the localized big model application architecture, the local knowledge base and indicator platform are used to perform prompt engineering on the local big model. Finally, based on the graphical question-and-answer interface and programming interface of the localized big model application architecture, natural language queries and programming methods are used to guide the local big model to generate osteoporosis disease database field sets and data production. Results The localized large model combined with the local knowledge base can summarize the fields involved in previous osteoporosis research and effectively improve the efficiency and quality of building a database for osteoporosis, but the processing results need to be manually verified. At the same time, based on the local large model, the local processing of multimodal data can be achieved, reducing the risk of medical data leakage.

  Key words: Disease-specific database; large model; local deployment; natural language understanding; unstructured data processing

  Submit time: 3 October 2024

  Copyright: The copyright holder for this preprint is the author/funder, who has granted biomedRxiv a license to display the preprint in perpetuity.
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• ID	Submit time	Number	Download
  2	2024-07-08	bmr.202410.00002V2	Download
  1	2024-07-08	bmr.202410.00002V1	Download

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